matlab-2005.dvi

Size: px
Start display at page:

Download "matlab-2005.dvi"

Transcription

1 I: MATLAB 2005 MATLAB 1. MATLAB 2. MATLAB 3. MATLAB kitahara/local/matlab/ 1 MATLAB 1.1 MATLAB MATLAB 1 FFT 1.2 MATLAB MATLAB PC Windows URL MATLAB Windows kitahara@kuis.kyoto-u.ac.jp 1

2 MATLAB UNIX %matlab MATLAB %matlab -nodesktop MATLAB MATLAB MATLAB >> quit 2

3 2 MATLAB 2.1 MATLAB >> ans = 8 >> 5-3 ans = 2 >> 5 * 3 ans = 15 >> 5 / 3 ans = >> 5 \ 3 ans = 0.6 >> 5 ^ 3 ans = 125 >> mod(5, 3) ans = 2 3

4 >> 1-3 * i ans = i >> a = 3; >> b = 2; >> a + b ans = 5 MATLAB MATLAB MATLAB whos >> whos Name Size Bytes Class a 1x1 8 double array b 1x1 8 double array ans 1x1 8 double array 4

5 >> x = [1 2 3] x = >> x = [1, 2, 3] x = >> x = [1; 2; 3] x = >> x = [1 2 3] x =

6 >> x = 1 : 10 x = >> x = (1 : 10) x = >> x = 1 : 2 : 10 x = >> x = (1 : 5) * 2 x =

7 >> A = [1 2 3; 4 5 6] A = >> A = [1 2 3; 4 5 6] A = >> A = [1 2; 3 4]; >> B = [5 6; 7 8]; >> A + B ans = >> A * B ans = >> A.* B ans = MATLAB * / \ ^.*./.\.^.+.- 7

8 1 { x +4y =1 2x +3y = 1 ( )( x y ) ( = 1 1 ) ( x y ) ( = ) 1 ( 1 1 ) >> [1 4; 2 3] \ [1; -1] ans = MATLAB zeros(m, n) 0 m n ones(m, n) 1 m n repmat(a, m, n) A m n find(a) A find(x>100) sum(a) A mean(a) A std(a) A 8

9 m MATLAB m ave.m function x = ave(a, b, c) x = (a + b + c) / 3; >> ave(6, 7, 8) ans = 7 if for while if a > 0 command1; elseif a == 0 command2; else command3; end for i = 1 : 10 x = x + i * i; fprintf(1, %d\n, x); end while result > 0 result = command(a, b, c); end & ~ any all 9

10 2.2 >> x = 0 : pi / 100 : 2 * pi; >> y = sin(x); >> plot(x, y); 2 >> x = 0 : pi / 10 : 2 * pi; >> y = sin(x); >> plot(x, y, o ); >> figure(2) 2 ID >> hold on >> figure 1 >> x = 0 : pi / 100 : 2 * pi; >> y = sin(x); >> plot(x, y); >> hold on >> x = 0 : pi / 10 : 2 * pi; >> y = sin(x); >> plot(x, y); >> hold off 10

11 2.3 MATLAB MATLAB for for 2 function S = test1(n) S = 0; for i = 1 : n S = S + i * i; end function S = test2(n) a = 1 : n; S = sum(a.* a); tic toc >> tic; test1(1000), toc >> tic; test2(1000), toc 2 for i = 1 : m for j = 1 : n A(i, j) = i * j; end end 11

12 2.4 MATLAB MATLAB char 1 n >> S = hello ; >> whos Name Size Bytes Class S 1x5 10 char array fprintf(id, S) ID id S id 1 C ischar(s) S isempty(s) S 0 0 strcmp(s 1, S 2 ) 2 S 1,S 2 strfind(s, p) S p num2str(x) x int2str(x) x str2num(x) x >> S1 = Hello ; >> S2 = World ; >> S = [S1 S2] S = HelloWorld >> S = [S1 S2] S = Hello World 12

13 fopen 1 fgetl fgets 2 mytype.m function mytype(filename) fid = fopen(filename, r ); while 1 line = fgetl(fid); if ~ischar(line) break; end fprintf(1, [line \n ]); end 3 strtok >> S = I have a pen ; >> [token, rest] = strtok(s) token = I rest = have a pen >> [token, rest2] = strtok(rest) token = have rest = a pen 13

14 3 (x, y, z) readxyz.m function [x, y, z] = readxyz(filename) fid = fopen(filename, r ); i = 1; while 1 line = fgetl(fid); if ~ischar(line) break; end [token, line] = strtok(line); x(i) = str2num(token); [token, line] = strtok(line); y(i) = str2num(token); [token, line] = strtok(line); z(i) = str2num(token); i = i + 1; end

15 2.5 GUI MATLAB GUI GUI GUI figure >> figure( Name, GUITest, Position, [ ],... Tag, GUITest, Risize, off ); figure figure(propertyname1, PropertyValue1, PropertyName2, PropertyName2,...) q Name Position [int int int int] x y Tag GUI Resize on / off GUI GUI uicontrol figure uicontrol(propertyname1, PropertyValue1, PropertyName2, PropertyName2,...) Style GUI pushbutton, togglebutton, radiobutton, checkbox, edit, text, slider, frame, listbox, popupmenu Position [int int int int] figure Tag figure String Value GUI GUI Callback MATLAB FontName FontSize MATLAB 15

16 4 1 GUI GUITest.m function GUITest fig = figure( Name, GUITest, Position, [ ],... Tag, GUITest, Resize, off ); slider = uicontrol( Style, slider, Position, [ ],... Tag, slider1, Callback, update ); edt = uicontrol( Style, edit, Position, [ ],... Tag, edt1 ); update.m update update 7 GUI GUI GUI Callback 1 Callback 2 Callback update update update.m function update % GUI GUI 3 findobj objhandle = findobj( Tag, TagValue) Tag TagValue GUI objhandle MATLAB set get 16

17 set set(objhandle, PropertyName, PropertyValue) objhandle GUI get x = get(objhandle, PropertyName) objhandle GUI 5 2 GUI update.m function update slider = findobj( Tag, slider1 ); edt = findobj( Tag, edt1 ); newvalue = get(slider, Value ); set(edt1, String, num2str(newvalue)); 8 3 GUI 2.6 >> help fft FFT Discrete Fourier transform. FFT(X) is the discrete Fourier transform (DFT) of vector X. For matrices, the FFT operation is applied to each column. For N-D arrays, the FFT operation operates on the first non-singleton dimension.... >> helpdesk 17

18 3 3.1 f A y = A sin(2πft) Hz >> t = 0 : 1/44100 : 5; >> y = 0.9 * sin(2 * pi * 440 * t); >> wavwrite(y, 44100, 16, test1.wav ); 9 262Hz Hz 2 3 >> t = 0 : 1/44100 : 5; >> y = 0.4 * sin(2 * pi * 440 * t) * sin(2 * pi * 880 * t) * sin(2 * pi * 1320 * t); >> wavwrite(y, 44100, 16, test2.wav ); GUI [ ] [ ] 12 18

19 FM FM y = A sin(2πf C t + I sin(2πf M t)). A f C, f M I sin sin sin FM 8 FM >> t = 0 : 1/44100 : 5; >> y = 0.9 * sin(2 * pi * 220 * t + sin(2 * pi * 880 * t)); >> wavwrite(y, 44100, 16, test3.wav ); 13 ( white noise) MATLAB randn >> fs = 44100; >> y = randn(1 * fs, 1); >> wavplay(y, fs); 14 19

20 >> t = 0 : 1/44100 : 2; >> A1 = linspace(0, 0.99, 0.02 / 44100); >> A2 = linspace(0.99, 0, length(t) / 44100); >> A = [A1 A2]; >> y = A.* sin(2 * pi * 440 * t); >> wavwrite(y, 44100, 16, test4.wav ); f * t f.* t 15 >> t = 0 : 1/44100 : 1; >> f = linspace(440, 880, length(t)); >> y = 0.9 * sin(2 * pi * f.* t); f * t f.* t amplitude modulation, AM frequency modulation, FM 1 20

21 3.2 MATLAB GUI GUI GUI AM FM 2 GUI Hz 660Hz 880Hz 220Hz 220Hz 11 21

22 ms /100 cent f[hz] f[cent] = 1200 log / sound1.txt sound1.txt

23 31 2 sound2.txt sound3.txt

24 3.3 (Fourier transform) f(t) f(t) F (ω) f(t) = 1 F (ω)e iωt dω 2π F (ω) F (ω) = f(t)exp(jωt)dt j (discrete Fourier transform; DFT) y(n) Y (e jω )= n y(n)exp( jωn) 2 (fast Fourier transform; FFT) 2 2 MATLAB 2 10 >> t = 0 : 1/44100 : 5; % >> y = 0.9 * sin(2 * pi * 440 * t); % 440Hz >> Y = fft(y); % >> f = linspace(0, 44100, length(y)); % >> plot(f, abs(y)); % 3 0 f s Hz f s 4 0 f s /2Hz 2 t n 3 abs 4 fhz 2fHz f shz f s/2hz 24

25 >> t = 0 : 1/44100 : 5; % >> y = 0.9 * sin(2 * pi * 440 * t); % 440Hz >> Y = fft(y); % >> Y = Y(1 : length(y) / 2 + 1); % >> f = linspace(0, 22050, length(y)); % >> plot(f, abs(y)); % (short-time Fourier transform, short-term Fourier transform; STFT) >> [y, fs, bits] = wavread( sample1.wav ); % sample1.wav >> y1 = y(1 * fs + (0 : 4095)); % >> Y1 = fft(y1); % >> Y1 = Y1(1 : length(y1) / 2 + 1); % >> f = linspace(0, fs/2, length(y)); % >> plot(f, abs(y)); % N { 1 (if 0 n N 1) w(n) = 0 (if n N) (rectangular window) N ( ) 2πn cos (if 0 n N 1) (Hanning window) w(n) = N 1 0 (if n N) ( ) 2 pin cos (if 0 n N 1) (Hamming window) w(n) = N 1 0 (if n N) (window function) 25

26 MATLAB hanning(n) hamming(n) >> [y, fs, bits] = wavread( sample1.wav ); % sample1.wav >> y1 = y(1 * fs + (0 : 4095)); % >> w = hanning(y1); % >> y1 = w.* y1; % >> Y1 = fft(y1); % >> Y1 = Y1(1 : length(y1) / 2 + 1); % >> f = linspace(0, fs/2, length(y)); % >> plot(f, abs(y)); % (spectrogram) MATLAB specgram specgram(y, N, f s, w, N overlap ) y N f s w N overlap >> [y, fs, bits] = wavread( sample1.wav ); % sample1.wav >> specgram(y, 4096, fs, hanning(4096), * fs); % 32 wav 33 specgram fft for specgram [Y, F] = specgram(y, N, f s, w, N overlap ) >> [y, fs, bits] = wavread( sample1.wav ); % sample1.wav >> [Y, F] = specgram(y, 4096, fs, hanning(4096), * fs); % >> plot(f, Y(:, 100)); % 1 26

27 3.4 2 function F0 = estimatef0(filename, th) [y, fs, bits] = wavread(filename); % sample1.wav [Y, F] = specgram(y, 4096, fs, hanning(4096), * fs); % Y = abs(y); Y(max(max(Y))./ Y > th) = 0; % for n = 1 : size(y, 2) Y1 = Y(:, n); dy1 = diff(y1); d2y1 = diff(dy1); s = sign(dy1(1 : end-1)).* sign(dy1(2 : end)); i = find(s == -1); i = i(d2y1(i) < 0); F0(n) = min(f(i)); end % n % % 2 % % % 2 pick up % 440Hz 440Hz 2 880Hz Hz 34 MATLAB y(t) τ y(t + τ) τ τ 35 MATLAB 27

28 y(t) g(t) v(t) Y (ω) Y (ω) = G(ω) V (ω). log Y (ω) = log G(ω) + log V (ω). k log Y k =log G k +log V k C n = 1 ( log G k exp j 2πkn ) + 1 N N N k ( log V k exp j 2πkn ) N (cepstrum coefficient) (quefrency) 36 MATLAB 37 MATLAB

29 L A TEX Word

30 5 MATLAB [1] Get Started with MATLAB, MATLAB [2] MATLAB [3] MATLAB [4] MATLAB CG [5] [6] CQ [7] MATLAB [8] MATLAB [9] H MATLAB DSP [10] Vol.56, No.2, pp ,

II - ( 02 ) 1,,,, 2, 3. ( ) HP,. 2 MATLAB MATLAB, C Java,,., MATLAB, Workspace, Workspace. Workspace who. whos. MATLAB, MATLAB Workspace. 2.1 Workspac

II - ( 02 ) 1,,,, 2, 3. ( ) HP,. 2 MATLAB MATLAB, C Java,,., MATLAB, Workspace, Workspace. Workspace who. whos. MATLAB, MATLAB Workspace. 2.1 Workspac II - ( 02 ) 1,,,, 2, 3 ( ) HP, 2 MATLAB MATLAB, C Java,,, MATLAB, Workspace, Workspace Workspace who whos MATLAB, MATLAB Workspace 21 Workspace 211 Workspace save, Workspace, MATLAB MAT, load, MAT Workspace

More information

2

2 16 1050026 1050042 1 2 1 1.1 3 1.2 3 1.3 3 2 2.1 4 2.2 4 2.2.1 5 2.2.2 5 2.3 7 2.3.1 1Basic 7 2.3.2 2 8 2.3.3 3 9 2.3.4 4window size 10 2.3.5 5 11 3 3.1 12 3.2 CCF 1 13 3.3 14 3.4 2 15 3.5 3 17 20 20 20

More information

(5 B m e i 2π T mt m m B m e i 2π T mt m m B m e i 2π T mt B m (m < 0 C m m (6 (7 (5 g(t C 0 + m C m e i 2π T mt (7 C m e i 2π T mt + m m C m e i 2π T

(5 B m e i 2π T mt m m B m e i 2π T mt m m B m e i 2π T mt B m (m < 0 C m m (6 (7 (5 g(t C 0 + m C m e i 2π T mt (7 C m e i 2π T mt + m m C m e i 2π T 2.6 FFT(Fast Fourier Transform 2.6. T g(t g(t 2 a 0 + { a m b m 2 T T 0 2 T T 0 (a m cos( 2π T mt + b m sin( 2π mt ( T m 2π g(t cos( T mtdt m 0,, 2,... 2π g(t sin( T mtdt m, 2, 3... (2 g(t T 0 < t < T

More information

数値計算:フーリエ変換

数値計算:フーリエ変換 ( ) 1 / 72 1 8 2 3 4 ( ) 2 / 72 ( ) 3 / 72 ( ) 4 / 72 ( ) 5 / 72 sample.m Fs = 1000; T = 1/Fs; L = 1000; t = (0:L-1)*T; % Sampling frequency % Sample time % Length of signal % Time vector y=1+0.7*sin(2*pi*50*t)+sin(2*pi*120*t)+2*randn(size(t));

More information

2 1 Octave Octave Window M m.m Octave Window 1.2 octave:1> a = 1 a = 1 octave:2> b = 1.23 b = octave:3> c = 3; ; % octave:4> x = pi x =

2 1 Octave Octave Window M m.m Octave Window 1.2 octave:1> a = 1 a = 1 octave:2> b = 1.23 b = octave:3> c = 3; ; % octave:4> x = pi x = 1 1 Octave GNU Octave Matlab John W. Eaton 1992 2.0.16 2.1.35 Octave Matlab gnuplot Matlab Octave MATLAB [1] Octave [1] 2.7 Octave Matlab Octave Octave 2.1.35 2.5 2.0.16 Octave 1.1 Octave octave Octave

More information

£Ã¥×¥í¥°¥é¥ß¥ó¥°(2018) - Âè11²ó – ½ÉÂꣲ¤Î²òÀ⡤±é½¬£² –

£Ã¥×¥í¥°¥é¥ß¥ó¥°(2018) - Âè11²ó – ½ÉÂꣲ¤Î²òÀ⡤±é½¬£² – (2018) 11 2018 12 13 2 g v dv x dt = bv x, dv y dt = g bv y (1) b v 0 θ x(t) = v 0 cos θ ( 1 e bt) (2) b y(t) = 1 ( v 0 sin θ + g ) ( 1 e bt) g b b b t (3) 11 ( ) p14 2 1 y 4 t m y > 0 y < 0 t m1 h = 0001

More information

2014 3 10 5 1 5 1.1..................................... 5 2 6 2.1.................................... 6 2.2 Z........................................ 6 2.3.................................. 6 2.3.1..................

More information

impulse_response.dvi

impulse_response.dvi 5 Time Time Level Level Frequency Frequency Fig. 5.1: [1] 2004. [2] P. A. Nelson, S. J. Elliott, Active Noise Control, Academic Press, 1992. [3] M. R. Schroeder, Integrated-impulse method measuring sound

More information

Ver.1 1/17/2003 2

Ver.1 1/17/2003 2 Ver.1 1/17/2003 1 Ver.1 1/17/2003 2 Ver.1 1/17/2003 3 Ver.1 1/17/2003 4 Ver.1 1/17/2003 5 Ver.1 1/17/2003 6 Ver.1 1/17/2003 MALTAB M GUI figure >> guide GUI GUI OK 7 Ver.1 1/17/2003 8 Ver.1 1/17/2003 Callback

More information

main.dvi

main.dvi 4 DFT DFT Fast Fourier Transform: FFT 4.1 DFT IDFT X(k) = 1 n=0 x(n)e j2πkn (4.1) 1 x(n) = 1 X(k)e j2πkn (4.2) k=0 x(n) X(k) DFT 2 ( 1) 2 4 2 2(2 1) 2 O( 2 ) 4.2 FFT 4.2.1 radix2 FFT 1 (4.1) 86 4. X(0)

More information

-- Blackman-Tukey FFT MEM Blackman-Tukey MEM MEM MEM MEM Singular Spectrum Analysis Multi-Taper Method (Matlab pmtm) 3... y(t) (Fourier transform) t=

-- Blackman-Tukey FFT MEM Blackman-Tukey MEM MEM MEM MEM Singular Spectrum Analysis Multi-Taper Method (Matlab pmtm) 3... y(t) (Fourier transform) t= --... 3..... 3...... 3...... 3..3....3 3..4....4 3..5....5 3.....6 3......6 3......7 3..3....0 3..4. Matlab... 3.3....3 3.3.....3 3.3.....4 3.3.3....4 3.3.4....5 3.3.5....5 3.4. MEM...8 3.4.. MEM...8 3.4..

More information

2.2 Sage I 11 factor Sage Sage exit quit 1 sage : exit 2 Exiting Sage ( CPU time 0m0.06s, Wall time 2m8.71 s). 2.2 Sage Python Sage 1. Sage.sage 2. sa

2.2 Sage I 11 factor Sage Sage exit quit 1 sage : exit 2 Exiting Sage ( CPU time 0m0.06s, Wall time 2m8.71 s). 2.2 Sage Python Sage 1. Sage.sage 2. sa I 2017 11 1 SageMath SageMath( Sage ) Sage Python Sage Python Sage Maxima Maxima Sage Sage Sage Linux, Mac, Windows *1 2 Sage Sage 4 1. ( sage CUI) 2. Sage ( sage.sage ) 3. Sage ( notebook() ) 4. Sage

More information

p = 1, 2, cos 2n + p)πj = cos 2nπj 2n + p)πj, sin = sin 2nπj 7.1) f j = a ) 0 + a p + a n+p cos 2nπj p=1 p=0 1 + ) b n+p p=0 sin 2nπj 1 2 a 0 +

p = 1, 2, cos 2n + p)πj = cos 2nπj 2n + p)πj, sin = sin 2nπj 7.1) f j = a ) 0 + a p + a n+p cos 2nπj p=1 p=0 1 + ) b n+p p=0 sin 2nπj 1 2 a 0 + 7 7.1 sound_wav_files flu00.wav.wav 44.1 khz 1/44100 spwave Text with Time spwave T > 0 t 44.1 khz t = 1 44100 j t f j {f 0, f 1, f 2,, f 1 = T t 7.2 T {f 0, f 1, f 2,, f 1 T ft) f j = fj t) j = 0, 1,

More information

Ver ceil floor FunctionGenerator (PTZCameraSony)

Ver ceil floor FunctionGenerator (PTZCameraSony) RT 2011 9 18 2009 11 15 1 2009 11 20 2009 12 4 1.2 Ver.1.0.2 ceil floor 3.2.1 4 FunctionGenerator 4.1 2009 12 7 4.2 2009 12 18 1.4 - - (PTZCameraSony) 2.2 - - 4.3 - - 2009 12 27 1.1 2011 9 18 OpenRTM-aist-1.0.0

More information

CDMA (high-compaciton multicarrier codedivision multiple access: HC/MC-CDMA),., HC/MC-CDMA,., 32.,, 64. HC/MC-CDMA, HC-MCM, i

CDMA (high-compaciton multicarrier codedivision multiple access: HC/MC-CDMA),., HC/MC-CDMA,., 32.,, 64. HC/MC-CDMA, HC-MCM, i 24 Investigation on HC/MC-CDMA Signals with Non-Uniform Frequency Intervals 1130401 2013 3 1 CDMA (high-compaciton multicarrier codedivision multiple access: HC/MC-CDMA),., HC/MC-CDMA,., 32.,, 64. HC/MC-CDMA,

More information

mstrcpy char *mstrcpy(const char *src); mstrcpy malloc (main free ) stdio.h fgets char *fgets(char *s, int size, FILE *stream); s size ( )

mstrcpy char *mstrcpy(const char *src); mstrcpy malloc (main free ) stdio.h fgets char *fgets(char *s, int size, FILE *stream); s size ( ) 2008 3 10 1 mstrcpy char *mstrcpy(const char *src); mstrcpy malloc (main free ) stdio.h fgets char *fgets(char *s, int size, FILE *stream); s size ( ) stream FILE ( man ) 40 ( ) %./a.out String : test

More information

6 6.1 sound_wav_files flu00.wav.wav 44.1 khz 1/44100 spwave Text with Time spwave t T = N t N 44.1 khz t = 1 sec j t f j {f 0, f 1, f 2,, f N 1

6 6.1 sound_wav_files flu00.wav.wav 44.1 khz 1/44100 spwave Text with Time spwave t T = N t N 44.1 khz t = 1 sec j t f j {f 0, f 1, f 2,, f N 1 6 6.1 sound_wav_files flu00.wav.wav 44.1 khz 1/44100 spwave Text with Time spwave t T = t 44.1 khz t = 1 sec 44100 j t f j {f 0, f 1, f 2,, f 1 6.2 T {f 0, f 1, f 2,, f 1 T ft) f j = fj t) j = 0, 1, 2,,

More information

A/B (2018/10/19) Ver kurino/2018/soft/soft.html A/B

A/B (2018/10/19) Ver kurino/2018/soft/soft.html A/B A/B (2018/10/19) Ver. 1.0 kurino@math.cst.nihon-u.ac.jp http://edu-gw2.math.cst.nihon-u.ac.jp/ kurino/2018/soft/soft.html 2018 10 19 A/B 1 2018 10 19 2 1 1 1.1 OHP.................................... 1

More information

1-4 int a; std::cin >> a; std::cout << "a = " << a << std::endl; C++( 1-4 ) stdio.h iostream iostream.h C++ include.h 1-4 scanf() std::cin >>

1-4 int a; std::cin >> a; std::cout << a =  << a << std::endl; C++( 1-4 ) stdio.h iostream iostream.h C++ include.h 1-4 scanf() std::cin >> 1 C++ 1.1 C C++ C++ C C C++ 1.1.1 C printf() scanf() C++ C hello world printf() 1-1 #include printf( "hello world\n" ); C++ 1-2 std::cout

More information

. (.8.). t + t m ü(t + t) + c u(t + t) + k u(t + t) = f(t + t) () m ü f. () c u k u t + t u Taylor t 3 u(t + t) = u(t) + t! u(t) + ( t)! = u(t) + t u(

. (.8.). t + t m ü(t + t) + c u(t + t) + k u(t + t) = f(t + t) () m ü f. () c u k u t + t u Taylor t 3 u(t + t) = u(t) + t! u(t) + ( t)! = u(t) + t u( 3 8. (.8.)............................................................................................3.............................................4 Nermark β..........................................

More information

web06.dvi

web06.dvi 73 6 MATLAB MATLAB GUI GUI M copyright c 2004 Tatsuya Kitamura / All rights reserved. 74 6 6.1 GUI MATLAB GUI property Windows MATLAB UNIX MATLAB GUI Graphical User Interface PC Red Hat Linux 5.2J Vine

More information

sp3.dvi

sp3.dvi 3 15 5 22 1 2 1.1... 2 1.2... 4 1.3... 5 1.4... 8 1.5 (Matlab )... 11 2 15 2.1... 15 2.2... 16 2.3... 17 3 19 3.1... 19 3.2... 2 3.3... 21 3.4... 22 3.5... 23 3.6... 24 3.7... 25 3.8 Daubechies... 26 4

More information

1.ppt

1.ppt /* * Program name: hello.c */ #include int main() { printf( hello, world\n ); return 0; /* * Program name: Hello.java */ import java.io.*; class Hello { public static void main(string[] arg)

More information

<4D F736F F D B B83578B6594BB2D834A836F815B82D082C88C60202E646F63>

<4D F736F F D B B83578B6594BB2D834A836F815B82D082C88C60202E646F63> 通信方式第 2 版 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. http://www.morikita.co.jp/books/mid/072662 このサンプルページの内容は, 第 2 版発行当時のものです. i 2 2 2 2012 5 ii,.,,,,,,.,.,,,,,.,,.,,..,,,,.,,.,.,,.,,.. 1990 5 iii 1 1

More information

コンピュータ概論

コンピュータ概論 4.1 For Check Point 1. For 2. 4.1.1 For (For) For = To Step (Next) 4.1.1 Next 4.1.1 4.1.2 1 i 10 For Next Cells(i,1) Cells(1, 1) Cells(2, 1) Cells(10, 1) 4.1.2 50 1. 2 1 10 3. 0 360 10 sin() 4.1.2 For

More information

Contents 1 Scilab

Contents 1 Scilab Scilab (Shuji Yoshikawa) December 18, 2017 Contents 1 Scilab 3 1.1..................................... 3 1.2..................................... 3 1.3....................................... 3 1.4............................

More information

超初心者用

超初心者用 3 1999 10 13 1. 2. hello.c printf( Hello, world! n ); cc hello.c a.out./a.out Hello, world printf( Hello, world! n ); 2 Hello, world printf n printf 3. ( ) int num; num = 100; num 100 100 num int num num

More information

卒 業 研 究 報 告.PDF

卒 業 研 究 報 告.PDF C 13 2 9 1 1-1. 1-2. 2 2-1. 2-2. 2-3. 2-4. 3 3-1. 3-2. 3-3. 3-4. 3-5. 3-5-1. 3-5-2. 3-6. 3-6-1. 3-6-2. 4 5 6 7-1 - 1 1 1-1. 1-2. ++ Lisp Pascal Java Purl HTML Windows - 2-2 2 2-1. 1972 D.M. (Dennis M Ritchie)

More information

[1] 1.1 x(t) t x(t + n ) = x(t) (n = 1,, 3, ) { x(t) : : 1 [ /, /] 1 x(t) = a + a 1 cos πt + a cos 4πt + + a n cos nπt + + b 1 sin πt + b sin 4πt = a

[1] 1.1 x(t) t x(t + n ) = x(t) (n = 1,, 3, ) { x(t) : : 1 [ /, /] 1 x(t) = a + a 1 cos πt + a cos 4πt + + a n cos nπt + + b 1 sin πt + b sin 4πt = a 13/7/1 II ( / A: ) (1) 1 [] (, ) ( ) ( ) ( ) etc. etc. 1. 1 [1] 1.1 x(t) t x(t + n ) = x(t) (n = 1,, 3, ) { x(t) : : 1 [ /, /] 1 x(t) = a + a 1 cos πt + a cos 4πt + + a n cos nπt + + b 1 sin πt + b sin

More information

main.dvi

main.dvi 3 Discrete Fourie Transform: DFT DFT 3.1 3.1.1 x(n) X(e jω ) X(e jω )= x(n)e jωnt (3.1) n= X(e jω ) N X(k) ωt f 2π f s N X(k) =X(e j2πk/n )= x(n)e j2πnk/n, k N 1 (3.2) n= X(k) δ X(e jω )= X(k)δ(ωT 2πk

More information

2004 2005 2 2 1G01P038-0 1 2 1.1.............................. 2 1.2......................... 2 1.3......................... 3 2 4 2.1............................ 4 2.2....................... 4 2.3.......................

More information

Hz

Hz ( ) 2006 1 3 3 3 4 10 Hz 1 1 1.1.................................... 1 1.2.................................... 1 2 2 2.1.................................... 2 2.2.................................... 3

More information

http://www.ike-dyn.ritsumei.ac.jp/ hyoo/wave.html 1 1, 5 3 1.1 1..................................... 3 1.2 5.1................................... 4 1.3.......................... 5 1.4 5.2, 5.3....................

More information

数値計算:常微分方程式

数値計算:常微分方程式 ( ) 1 / 82 1 2 3 4 5 6 ( ) 2 / 82 ( ) 3 / 82 C θ l y m O x mg λ ( ) 4 / 82 θ t C J = ml 2 C mgl sin θ θ C J θ = mgl sin θ = θ ( ) 5 / 82 ω = θ J ω = mgl sin θ ω J = ml 2 θ = ω, ω = g l sin θ = θ ω ( )

More information

num2.dvi

num2.dvi kanenko@mbk.nifty.com http://kanenko.a.la9.jp/ 16 32...... h 0 h = ε () 0 ( ) 0 1 IEEE754 (ieee754.c Kerosoft Ltd.!) 1 2 : OS! : WindowsXP ( ) : X Window xcalc.. (,.) C double 10,??? 3 :, ( ) : BASIC,

More information

1.3 2 gnuplot> set samples gnuplot> plot sin(x) sin gnuplot> plot [0:6.28] [-1.5:1.5] sin(x) gnuplot> plot [-6.28:6.28] [-1.5:1.5] sin(x),co

1.3 2 gnuplot> set samples gnuplot> plot sin(x) sin gnuplot> plot [0:6.28] [-1.5:1.5] sin(x) gnuplot> plot [-6.28:6.28] [-1.5:1.5] sin(x),co gnuplot 8 gnuplot 1 1.1 gnuplot gnuplot 2D 3D gnuplot ( ) gnuplot UNIX Windows Machintosh Excel gnuplot C 1.2 web gnuplot $ gnuplot gnuplot gnuplot> exit 1 1.3 2 gnuplot> set samples 1024 1024 gnuplot>

More information

double 2 std::cin, std::cout 1.2 C fopen() fclose() C++ std::fstream 1-3 #include <fstream> std::fstream fout; int a = 123; fout.open( "data.t

double 2 std::cin, std::cout 1.2 C fopen() fclose() C++ std::fstream 1-3 #include <fstream> std::fstream fout; int a = 123; fout.open( data.t C++ 1 C C++ C++ C C C++ 1.1 C printf() scanf() C++ C 1-1 #include int a; scanf( "%d", &a ); printf( "a = %d\n", a ); C++ 1-2 int a; std::cin >> a; std::cout

More information

1 KC KC H.13 1. 3 2. 4 3. 5 3.1. 5 3.2. 6 4. 7 4.1. 8 4.1.1. 8 4.1.2. 9 4.1.3. 10 4.1.4. MATLAB 11 4.1.5. 20 4.1.6. 21 4.1.7. 26 4.2. 28 4.2.1. 28 4.2.2. 30 4.2.3. 31 4.2.4. 36 4.3. 37 5. 40 5.1. 40 5.2.

More information

Microsoft Word - 信号処理3.doc

Microsoft Word - 信号処理3.doc Junji OHTSUBO 2012 FFT FFT SN sin cos x v ψ(x,t) = f (x vt) (1.1) t=0 (1.1) ψ(x,t) = A 0 cos{k(x vt) + φ} = A 0 cos(kx ωt + φ) (1.2) A 0 v=ω/k φ ω k 1.3 (1.2) (1.2) (1.2) (1.1) 1.1 c c = a + ib, a = Re[c],

More information

pp d 2 * Hz Hz 3 10 db Wind-induced noise, Noise reduction, Microphone array, Beamforming 1

pp d 2 * Hz Hz 3 10 db Wind-induced noise, Noise reduction, Microphone array, Beamforming 1 72 12 2016 pp. 739 748 739 43.60.+d 2 * 1 2 2 3 2 125 Hz 0.3 0.8 2 125 Hz 3 10 db Wind-induced noise, Noise reduction, Microphone array, Beamforming 1. 1.1 PSS [1] [2 4] 2 Wind-induced noise reduction

More information

Report C: : ( )

Report C: : ( ) Report2 045713C: : 18 07 23 ( ) 1 3 SCILAB (lpc.sci) Hamming DTF LPC (Levinson-Durbin ) LPC (1) (2) Levinson-Durbin SCILAB lev() SCILAB (3) =0 roots() 0 5KHz 0 5KHz (4) 100 300 8 20 (5) pre emp 1.0 2 fft_len=512;

More information

ex14.dvi

ex14.dvi 1,, 0, b (b b 2 b ) n k n = n j b j, (0 n j b 1), n =(n k n k 1...n 1 n 0 ) b, n j j j +1, 0,...,b 1 (digit). b b, n b 1 ñ, ñ = k (b 1 n j )b j b N, n b n, n = b N n, n =ñ+1 b N, n m n + m (mod b N ),

More information

untitled

untitled JPEG yoshi@image.med.osaka u.ac.jp http://www.image.med.osaka u.ac.jp/member/yoshi/ (Computer Graphics: CG) (Virtual/Augmented(Mixed) Reality: VR AR MR) (Computer Graphics: CG) (Virtual/Augmented(Mixed)

More information

Excel ではじめる数値解析 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. このサンプルページの内容は, 初版 1 刷発行時のものです.

Excel ではじめる数値解析 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます.   このサンプルページの内容は, 初版 1 刷発行時のものです. Excel ではじめる数値解析 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. http://www.morikita.co.jp/books/mid/009631 このサンプルページの内容は, 初版 1 刷発行時のものです. Excel URL http://www.morikita.co.jp/books/mid/009631 i Microsoft Windows

More information

N88 BASIC 0.3 C: My Documents 0.6: 0.3: (R) (G) : enterreturn : (F) BA- SIC.bas 0.8: (V) 0.9: 0.5:

N88 BASIC 0.3 C: My Documents 0.6: 0.3: (R) (G) : enterreturn : (F) BA- SIC.bas 0.8: (V) 0.9: 0.5: BASIC 20 4 10 0 N88 Basic 1 0.0 N88 Basic..................................... 1 0.1............................................... 3 1 4 2 5 3 6 4 7 5 10 6 13 7 14 0 N88 Basic 0.0 N88 Basic 0.1: N88Basic

More information

For_Beginners_CAPL.indd

For_Beginners_CAPL.indd CAPL Vector Japan Co., Ltd. 目次 1 CAPL 03 2 CAPL 03 3 CAPL 03 4 CAPL 04 4.1 CAPL 4.2 CAPL 4.3 07 5 CAPL 08 5.1 CANoe 5.2 CANalyzer 6 CAPL 10 7 CAPL 11 7.1 CAPL 7.2 CAPL 7.3 CAPL 7.4 CAPL 16 7.5 18 8 CAPL

More information

K227 Java 2

K227 Java 2 1 K227 Java 2 3 4 5 6 Java 7 class Sample1 { public static void main (String args[]) { System.out.println( Java! ); } } 8 > javac Sample1.java 9 10 > java Sample1 Java 11 12 13 http://java.sun.com/j2se/1.5.0/ja/download.html

More information

CPU Levels in the memory hierarchy Level 1 Level 2... Increasing distance from the CPU in access time Level n Size of the memory at each level 1: 2.2

CPU Levels in the memory hierarchy Level 1 Level 2... Increasing distance from the CPU in access time Level n Size of the memory at each level 1: 2.2 FFT 1 Fourier fast Fourier transform FFT FFT FFT 1 FFT FFT 2 Fourier 2.1 Fourier FFT Fourier discrete Fourier transform DFT DFT n 1 y k = j=0 x j ω jk n, 0 k n 1 (1) x j y k ω n = e 2πi/n i = 1 (1) n DFT

More information

1 Fourier Fourier Fourier Fourier Fourier Fourier Fourier Fourier Fourier analog digital Fourier Fourier Fourier Fourier Fourier Fourier Green Fourier

1 Fourier Fourier Fourier Fourier Fourier Fourier Fourier Fourier Fourier analog digital Fourier Fourier Fourier Fourier Fourier Fourier Green Fourier Fourier Fourier Fourier etc * 1 Fourier Fourier Fourier (DFT Fourier (FFT Heat Equation, Fourier Series, Fourier Transform, Discrete Fourier Transform, etc Yoshifumi TAKEDA 1 Abstract Suppose that u is

More information

1 s(t) ( ) f c : A cos(2πf c t + ϕ) (AM, Amplitude Modulation) (FM, Frequency Modulation) (PM, Phase Modulation) 2

1 s(t) ( ) f c : A cos(2πf c t + ϕ) (AM, Amplitude Modulation) (FM, Frequency Modulation) (PM, Phase Modulation) 2 (Communication and Network) 1 1 s(t) ( ) f c : A cos(2πf c t + ϕ) (AM, Amplitude Modulation) (FM, Frequency Modulation) (PM, Phase Modulation) 2 1.1 AM s(t) : A(αs(t) + 1) cos 2πf c t A, α : s(t) = cos

More information

Input image Initialize variables Loop for period of oscillation Update height map Make shade image Change property of image Output image Change time L

Input image Initialize variables Loop for period of oscillation Update height map Make shade image Change property of image Output image Change time L 1,a) 1,b) 1/f β Generation Method of Animation from Pictures with Natural Flicker Abstract: Some methods to create animation automatically from one picture have been proposed. There is a method that gives

More information

C

C C 1 2 1.1........................... 2 1.2........................ 2 1.3 make................................................ 3 1.4....................................... 5 1.4.1 strip................................................

More information

I J

I J I 065763J 8 7 7 31 jikken/ +----- accumulation_demupa.c +----- accumulation_rain.c +----- frequency_demupa.c +----- frequency_rain.c +----- go.sh +----- graph_maker.sh +----- mesure-ryudai/ 2007/4/1 2007/6/30

More information

1 2 2 (POC)

1 2 2 (POC) 2007 Taichi Kawasaki Kinki University School of Engineerings 1 2 2 (POC) 6 3 7 4 12 5 13 6 18 7 24 8 26 9 27 10 31 1 1 [1]. 1 [2] P.Chazal [3] 2 3 2 1: 3 2: 4 3: 5 2 (POC) f(n 1, n 2 ) g(n 1, n 2 ) 2 F

More information

main.dvi

main.dvi 6 FIR FIR FIR FIR 6.1 FIR 6.1.1 H(e jω ) H(e jω )= H(e jω ) e jθ(ω) = H(e jω ) (cos θ(ω)+jsin θ(ω)) (6.1) H(e jω ) θ(ω) θ(ω) = KωT, K > 0 (6.2) 6.1.2 6.1 6.1 FIR 123 6.1 H(e jω 1, ω

More information

TSP信号を用いた音響系評価の研究

TSP信号を用いた音響系評価の研究 1 TSP 98kc068 2 1. 4 2. TSP 2.1 2.2 TSP 2.2.1 ATSP 2.2.2 OATSP 2.3 N 3. 5 5 6 6 7 8 2.3.1 N 8 2.3.2 TSP 9 2.3.3 2.3.4 m 3.1 3.1.1 3.1.2 3.2 3.3 15 18 20 20 20 21 22 24 3.3.1 24 3.3.2 3.4 3.4.1 3.4.2 4.

More information

£Ã¥×¥í¥°¥é¥ß¥ó¥°ÆþÌç (2018) - Â裱£²²ó ¡Ý½ÉÂꣲ¤Î²òÀ⡤±é½¬£²¡Ý

£Ã¥×¥í¥°¥é¥ß¥ó¥°ÆþÌç (2018) - Â裱£²²ó  ¡Ý½ÉÂꣲ¤Î²òÀ⡤±é½¬£²¡Ý (2018) 2018 7 5 f(x) [ 1, 1] 3 3 1 3 f(x) dx c i f(x i ) 1 0 i=1 = 5 ) ( ) 3 ( 9 f + 8 5 9 f(0) + 5 3 9 f 5 1 1 + sin(x) θ ( 1 θ dx = tan 1 + sin x 2 π ) + 1 4 1 3 [a, b] f a, b double G3(double (*f)(),

More information

85 4

85 4 85 4 86 Copright c 005 Kumanekosha 4.1 ( ) ( t ) t, t 4.1.1 t Step! (Step 1) (, 0) (Step ) ±V t (, t) I Check! P P V t π 54 t = 0 + V (, t) π θ : = θ : π ) θ = π ± sin ± cos t = 0 (, 0) = sin π V + t +V

More information

1 1 sin cos P (primary) S (secondly) 2 P S A sin(ω2πt + α) A ω 1 ω α V T m T m 1 100Hz m 2 36km 500Hz. 36km 1

1 1 sin cos P (primary) S (secondly) 2 P S A sin(ω2πt + α) A ω 1 ω α V T m T m 1 100Hz m 2 36km 500Hz. 36km 1 sin cos P (primary) S (secondly) 2 P S A sin(ω2πt + α) A ω ω α 3 3 2 2V 3 33+.6T m T 5 34m Hz. 34 3.4m 2 36km 5Hz. 36km m 34 m 5 34 + m 5 33 5 =.66m 34m 34 x =.66 55Hz, 35 5 =.7 485.7Hz 2 V 5Hz.5V.5V V

More information

Microsoft PowerPoint - MATLABの使い方.ppt

Microsoft PowerPoint - MATLABの使い方.ppt MATLAB の使い方 東京大学橋梁研究室 MATLAB とは 技術計算のための高性能言語 特徴配列が基本的データ要素変数宣言不要. 対話的システム. 豊富な関数ライブラリ, グラフィックスツール. 使用される分野 数値計算, アルゴリズムの開発, モデル化, シミュレーション, データ解析,GUI アプリケーションの開発, グラフィックス, etc. MATLAB の動かし方 1 コマンドウィンドウにプログラムを打ち込み,

More information

untitled

untitled II yacc 005 : 1, 1 1 1 %{ int lineno=0; 3 int wordno=0; 4 int charno=0; 5 6 %} 7 8 %% 9 [ \t]+ { charno+=strlen(yytext); } 10 "\n" { lineno++; charno++; } 11 [^ \t\n]+ { wordno++; charno+=strlen(yytext);}

More information

Z: Q: R: C: sin 6 5 ζ a, b

Z: Q: R: C: sin 6 5 ζ a, b Z: Q: R: C: 3 3 7 4 sin 6 5 ζ 9 6 6............................... 6............................... 6.3......................... 4 7 6 8 8 9 3 33 a, b a bc c b a a b 5 3 5 3 5 5 3 a a a a p > p p p, 3,

More information

2: 3: A, f, φ f(t = A sin(2πft + φ = A sin(ωt + φ ω 2πf 440Hz A ( ( 4 ( 5 f(t = sin(2πf 1t + sin(2πf 2 t = 2 sin(2πt(f 1 + f 2 /2 cos(2πt(f 1 f

2: 3: A, f, φ f(t = A sin(2πft + φ = A sin(ωt + φ ω 2πf 440Hz A ( ( 4 ( 5 f(t = sin(2πf 1t + sin(2πf 2 t = 2 sin(2πt(f 1 + f 2 /2 cos(2πt(f 1 f 12 ( TV TV, CATV, CS CD, DAT, DV, DVD ( 12.1 12.1.1 1 1: T (sec f (Hz T= 1 f P a = N/m 2 1.013 10 5 P a 1 10 5 1.00001 0.99999 2,3 1 2: 3: 12.1.2 A, f, φ f(t = A sin(2πft + φ = A sin(ωt + φ ω 2πf 440Hz

More information

Appendix A BASIC BASIC Beginner s All-purpose Symbolic Instruction Code FORTRAN COBOL C JAVA PASCAL (NEC N88-BASIC Windows BASIC (1) (2) ( ) BASIC BAS

Appendix A BASIC BASIC Beginner s All-purpose Symbolic Instruction Code FORTRAN COBOL C JAVA PASCAL (NEC N88-BASIC Windows BASIC (1) (2) ( ) BASIC BAS Appendix A BASIC BASIC Beginner s All-purpose Symbolic Instruction Code FORTRAN COBOL C JAVA PASCAL (NEC N88-BASIC Windows BASIC (1 (2 ( BASIC BASIC download TUTORIAL.PDF http://hp.vector.co.jp/authors/va008683/

More information

Abstract This paper concerns with a method of dynamic image cognition. Our image cognition method has two distinguished features. One is that the imag

Abstract This paper concerns with a method of dynamic image cognition. Our image cognition method has two distinguished features. One is that the imag 2004 RGB A STUDY OF RGB COLOR INFORMATION AND ITS APPLICATION 03R3237 Abstract This paper concerns with a method of dynamic image cognition. Our image cognition method has two distinguished features. One

More information

pptx

pptx iphone 2010 8 18 C xkozima@myu.ac.jp C Hello, World! Hello World hello.c! printf( Hello, World!\n );! os> ls! hello.c! os> cc hello.c o hello! os> ls! hello!!hello.c! os>./hello! Hello, World!! os>! os>

More information

GPS GPS GPS GPS GPS

GPS GPS GPS GPS GPS 22 GPS/QZSS 0723053 1... 4 1.1... 4 1.2... 4 1.3 GPS... 4 1.4 GPS... 6 1.5... 12 2 GPS... 16 2.1 GPS... 16 2.2 GPS... 16 2.3... 17 2.3... 18 2.4... 21 2.5... 24 2.6... 26 3 GPS... 28 3.1 DGPS... 28 3.1.1...

More information

WinHPC ppt

WinHPC ppt MPI.NET C# 2 2009 1 20 MPI.NET MPI.NET C# MPI.NET C# MPI MPI.NET 1 1 MPI.NET C# Hello World MPI.NET.NET Framework.NET C# API C# Microsoft.NET java.net (Visual Basic.NET Visual C++) C# class Helloworld

More information

,, 2. Matlab Simulink 2018 PC Matlab Scilab 2

,, 2. Matlab Simulink 2018 PC Matlab Scilab 2 (2018 ) ( -1) TA Email : ohki@i.kyoto-u.ac.jp, ske.ta@bode.amp.i.kyoto-u.ac.jp : 411 : 10 308 1 1 2 2 2.1............................................ 2 2.2..................................................

More information

Original : Hello World! (0x0xbfab85e0) Copy : Hello World! (0x0x804a050) fgets mstrcpy malloc mstrcpy (main ) mstrcpy malloc free fgets stream 1 ( \n

Original : Hello World! (0x0xbfab85e0) Copy : Hello World! (0x0x804a050) fgets mstrcpy malloc mstrcpy (main ) mstrcpy malloc free fgets stream 1 ( \n 2008 3 10 1 mstrcpy char *mstrcpy(const char *src); mstrcpy malloc (main free ) stdio.h fgets char *fgets(char *s, int size, FILE *stream); s size ( ) stream FILE ( man ) 40 ( ) %./a.out String : test

More information

Copyright c 2008 Zhenjiang Hu, All Right Reserved.

Copyright c 2008 Zhenjiang Hu, All Right Reserved. 2008 10 27 Copyright c 2008 Zhenjiang Hu, All Right Reserved. (Bool) True False data Bool = False True Remark: not :: Bool Bool not False = True not True = False (Pattern matching) (Rewriting rules) not

More information

1. ( ) 1.1 t + t [m]{ü(t + t)} + [c]{ u(t + t)} + [k]{u(t + t)} = {f(t + t)} (1) m ü f c u k u 1.2 Newmark β (1) (2) ( [m] + t ) 2 [c] + β( t)2

1. ( ) 1.1 t + t [m]{ü(t + t)} + [c]{ u(t + t)} + [k]{u(t + t)} = {f(t + t)} (1) m ü f c u k u 1.2 Newmark β (1) (2) ( [m] + t ) 2 [c] + β( t)2 212 1 6 1. (212.8.14) 1 1.1............................................. 1 1.2 Newmark β....................... 1 1.3.................................... 2 1.4 (212.8.19)..................................

More information

OpenCV IS Report No Report Medical Information System Labratry

OpenCV IS Report No Report Medical Information System Labratry OpenCV 2014 8 25 IS Report No. 2014090201 Report Medical Information System Labratry Abstract OpenCV OpenCV 1............................ 2 1.1 OpenCV.......................... 2 1.2......................

More information

1 P2 P P3P4 P5P8 P9P10 P11 P12

1 P2 P P3P4 P5P8 P9P10 P11 P12 1 P2 P14 2 3 4 5 1 P3P4 P5P8 P9P10 P11 P12 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 & 11 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1! 3 2 3! 4 4 3 5 6 I 7 8 P7 P7I P5 9 P5! 10 4!! 11 5 03-5220-8520

More information

GraphicsWithPlotFull.nb Plot[{( 1), ( ),...}, {( ), ( ), ( )}] Plot Plot Cos x Sin x, x, 5 Π, 5 Π, AxesLabel x, y x 1 Plot AxesLabel

GraphicsWithPlotFull.nb Plot[{( 1), ( ),...}, {( ), ( ), ( )}] Plot Plot Cos x Sin x, x, 5 Π, 5 Π, AxesLabel x, y x 1 Plot AxesLabel http://yktlab.cis.k.hosei.ac.jp/wiki/ 1(Plot) f x x x 1 1 x x ( )[( 1)_, ( )_, ( 3)_,...]=( ) Plot Plot f x, x, 5, 3 15 10 5 Plot[( ), {( ), ( ), ( )}] D g x x 3 x 3 Plot f x, g x, x, 10, 8 00 100 10 5

More information

橡実験IIINMR.PDF

橡実験IIINMR.PDF (NMR) 0 (NMR) 2µH hω ω 1 h 2 1 1-1 NMR NMR h I µ = γµ N 1-2 1 H 19 F Ne µ = Neh 2mc ( 1) N 2 ( ) I =1/2 I =3/2 I z =+1/2 I z = 1/2 γh H>0 2µH H=0 µh I z =+3/2 I z =+1/2 I z = 1/2 I z = 3/2 γh H>0 2µH H=0

More information

筑波大学大学院博士課程

筑波大学大学院博士課程 3. 3. 4 6. 6. 7.3 8 3 9 3. 9 3. 3 3.3 3 3.4 6 4 7 4. 7 4. 7 4.3 4.4 5 5 5. 5 5. 5 5.3 3 6 4 6. 4 6-43 6. 44 6.3 46 6.4 47 7 48 49 5 5 . [] 3 [] [3-] 3 . [-] [5] [3] 5kHz [8] 3.6Hz 3 4 5 6 5 7 4 Fig. -

More information

°ÌÁê¿ô³ØII

°ÌÁê¿ô³ØII July 14, 2007 Brouwer f f(x) = x x f(z) = 0 2 f : S 2 R 2 f(x) = f( x) x S 2 3 3 2 - - - 1. X x X U(x) U(x) x U = {U(x) x X} X 1. U(x) A U(x) x 2. A U(x), A B B U(x) 3. A, B U(x) A B U(x) 4. A U(x),

More information

2005年度卒業論文

2005年度卒業論文 005 GPS 107 000 GPS (Global Positioning System) GPS GPS GPS GPS GPS 1 GPS GPS 3 GPS GPS 1GPS GPS GPS 1 1.1 GPS.1.1 GPS.1. GPS 3.1.3 9.1.4 11.1.5 13. 14..1 14.. 14..3 15..4 17 1) 17 ) 17 3) 18..5 19.4 GPS

More information

I I / 68

I I / 68 2013.07.04 I 2013 3 I 2013.07.04 1 / 68 I 2013.07.04 2 / 68 I 2013.07.04 3 / 68 heat1.f90 heat2.f90 /tmp/130704/heat2.f90 I 2013.07.04 4 / 68 diff heat1.f90 heat2.f90!! heat2. f 9 0! c m > NGRID! c nmax

More information

LCR e ix LC AM m k x m x x > 0 x < 0 F x > 0 x < 0 F = k x (k > 0) k x = x(t)

LCR e ix LC AM m k x m x x > 0 x < 0 F x > 0 x < 0 F = k x (k > 0) k x = x(t) 338 7 7.3 LCR 2.4.3 e ix LC AM 7.3.1 7.3.1.1 m k x m x x > 0 x < 0 F x > 0 x < 0 F = k x k > 0 k 5.3.1.1 x = xt 7.3 339 m 2 x t 2 = k x 2 x t 2 = ω 2 0 x ω0 = k m ω 0 1.4.4.3 2 +α 14.9.3.1 5.3.2.1 2 x

More information

: Shift-Return evaluate 2.3 Sage? Shift-Return abs 2 abs? 2: abs 3: fac

: Shift-Return evaluate 2.3 Sage? Shift-Return abs 2 abs? 2: abs 3: fac Bulletin of JSSAC(2012) Vol. 18, No. 2, pp. 161-171 : Sage 1 Sage Mathematica Sage (William Stein) 2005 2 2006 2 UCSD Sage Days 1 Sage 1.0 4.7.2 1) Sage Maxima, R 2 Sage Firefox Internet Explorer Sage

More information

Gmech08.dvi

Gmech08.dvi 145 13 13.1 13.1.1 0 m mg S 13.1 F 13.1 F /m S F F 13.1 F mg S F F mg 13.1: m d2 r 2 = F + F = 0 (13.1) 146 13 F = F (13.2) S S S S S P r S P r r = r 0 + r (13.3) r 0 S S m d2 r 2 = F (13.4) (13.3) d 2

More information

USB 0.6 https://duet.doshisha.ac.jp/info/index.jsp 2 ID TA DUET 24:00 DUET XXX -YY.c ( ) XXX -YY.txt() XXX ID 3 YY ID 5 () #define StudentID 231

USB 0.6 https://duet.doshisha.ac.jp/info/index.jsp 2 ID TA DUET 24:00 DUET XXX -YY.c ( ) XXX -YY.txt() XXX ID 3 YY ID 5 () #define StudentID 231 0 0.1 ANSI-C 0.2 web http://www1.doshisha.ac.jp/ kibuki/programming/resume p.html 0.3 2012 1 9/28 0 [ 01] 2 10/5 1 C 2 3 10/12 10 1 2 [ 02] 4 10/19 3 5 10/26 3 [ 03] 6 11/2 3 [ 04] 7 11/9 8 11/16 4 9 11/30

More information

untitled

untitled 1 SS 2 2 (DS) 3 2.1 DS................................ 3 2.2 DS................................ 4 2.3.................................. 4 2.4 (channel papacity)............................ 6 2.5........................................

More information

05 I I / 56

05 I I / 56 05 I 2015 2015.05.14 I 05 2015.05.14 1 / 56 I 05 2015.05.14 2 / 56 cd mkdir vis01 OK cd vis01 cp /tmp/150514/leibniz.*. I 05 2015.05.14 3 / 56 I 05 2015.05.14 4 / 56 Information visualization Data visualization,

More information

RIMS98R2.dvi

RIMS98R2.dvi RIMS Kokyuroku, vol.084, (999), 45 59. Euler Fourier Euler Fourier S = ( ) n f(n) = e in f(n) (.) I = 0 e ix f(x) dx (.2) Euler Fourier Fourier Euler Euler Fourier Euler Euler Fourier Fourier [5], [6]

More information

2 MATLABについて n MATLABとは 科 学 技 術 計 算 のための 高 性 能 プログラミング 言 語 n 特 徴 配 列 が 基 本 データ 型 ベクトル(1 次 元 配 列 ) 行 列 (2 次 元 配 列 ) 対 話 的 システム 豊 富 な 関 数 ライブラリとグラフィックツー

2 MATLABについて n MATLABとは 科 学 技 術 計 算 のための 高 性 能 プログラミング 言 語 n 特 徴 配 列 が 基 本 データ 型 ベクトル(1 次 元 配 列 ) 行 列 (2 次 元 配 列 ) 対 話 的 システム 豊 富 な 関 数 ライブラリとグラフィックツー 2016 年 5 月 31 日 版 MATLABの 基 本 的 な 使 い 方 担 当 : 荻 田 武 史 2 MATLABについて n MATLABとは 科 学 技 術 計 算 のための 高 性 能 プログラミング 言 語 n 特 徴 配 列 が 基 本 データ 型 ベクトル(1 次 元 配 列 ) 行 列 (2 次 元 配 列 ) 対 話 的 システム 豊 富 な 関 数 ライブラリとグラフィックツール

More information

1 1 2 1 2.1.......................... 1 2.1.1........................... 2 2.1.2....................... 2 3 4 4 5 4.1.................................

1 1 2 1 2.1.......................... 1 2.1.1........................... 2 2.1.2....................... 2 3 4 4 5 4.1................................. CUI 13 2 14 1 1 2 1 2.1.......................... 1 2.1.1........................... 2 2.1.2....................... 2 3 4 4 5 4.1................................. 5 4.1.1...................... 5 4.1.2.......................

More information

1 C STL(1) C C C libc C C C++ STL(Standard Template Library ) libc libc C++ C STL libc STL iostream Algorithm libc STL string vector l

1 C STL(1) C C C libc C C C++ STL(Standard Template Library ) libc libc C++ C STL libc STL iostream Algorithm libc STL string vector l C/C++ 2007 6 18 1 C STL(1) 2 1.1............................................... 2 1.2 stdio................................................ 3 1.3.......................................... 10 2 11 2.1 sizeof......................................

More information

RT300i/RT140x/RT105i 取扱説明書

RT300i/RT140x/RT105i 取扱説明書 2 3 4 5 6 7 8 9 10 Bold face Enter Ctrl Tab BS Del Typewriter face RT105i RT300i RT140p RT140f RT140i RT140e RT105i RT300i 11 RARP 9600 bit/s 8 http://www.rtpro.yamaha.co.jp/ ftp.rtpro.yamaha.co.jp 12

More information

Microsoft Word - scilab_intro.doc

Microsoft Word - scilab_intro.doc Scilab の使い方 (1/14) Scilab は "SCIence LABoratory" の略 フランスの国立研究機関 INRIA (Institut National de Recherche en Informatique et Automatique) が作成 配布しているフリーのシミュレーション ソフト Scilab のホームページは http://www-rocq.inria.fr/scilab/

More information

main.dvi

main.dvi MATLAB DCS MATLAB/Simulink MATLAB/Simulink MATLAB Simulink MATLAB/Simulink DCS 1 MATLAB Simulink 2 MATLAB Simulink 3 MAT- LAB/Simulink 4 MATLAB/Simulink ii PID 5 2 43 MATLAB 6 MATLAB 7 MATLAB 8 DCS MATLAB

More information

18 C ( ) hello world.c 1 #include <stdio.h> 2 3 main() 4 { 5 printf("hello World\n"); 6 } [ ] [ ] #include <stdio.h> % cc hello_world.c %./a.o

18 C ( ) hello world.c 1 #include <stdio.h> 2 3 main() 4 { 5 printf(hello World\n); 6 } [ ] [ ] #include <stdio.h> % cc hello_world.c %./a.o 18 C ( ) 1 1 1.1 hello world.c 5 printf("hello World\n"); 6 } [ ] [ ] #include % cc hello_world.c %./a.out Hello World [a.out ] % cc hello_world.c -o hello_world [ ( ) ] (K&R 4.1.1) #include

More information

1. A0 A B A0 A : A1,...,A5 B : B1,...,B

1. A0 A B A0 A : A1,...,A5 B : B1,...,B 1. A0 A B A0 A : A1,...,A5 B : B1,...,B12 2. 3. 4. 5. A0 A, B Z Z m, n Z m n m, n A m, n B m=n (1) A, B (2) A B = A B = Z/ π : Z Z/ (3) A B Z/ (4) Z/ A, B (5) f : Z Z f(n) = n f = g π g : Z/ Z A, B (6)

More information

1 1 [1] ( 2,625 [2] ( 2, ( ) /

1 1 [1] ( 2,625 [2] ( 2, ( ) / [] (,65 [] (,3 ( ) 67 84 76 7 8 6 7 65 68 7 75 73 68 7 73 7 7 59 67 68 65 75 56 6 58 /=45 /=45 6 65 63 3 4 3/=36 4/=8 66 7 68 7 7/=38 /=5 7 75 73 8 9 8/=364 9/=864 76 8 78 /=45 /=99 8 85 83 /=9 /= ( )

More information

untitled

untitled 2 : n =1, 2,, 10000 0.5125 0.51 0.5075 0.505 0.5025 0.5 0.4975 0.495 0 2000 4000 6000 8000 10000 2 weak law of large numbers 1. X 1,X 2,,X n 2. µ = E(X i ),i=1, 2,,n 3. σi 2 = V (X i ) σ 2,i=1, 2,,n ɛ>0

More information

画像工学特論

画像工学特論 .? (x i, y i )? (x(t), y(t))? (x(t)) (X(ω)) Wiener-Khintchine 35/97 . : x(t) = X(ω)e jωt dω () π X(ω) = x(t)e jωt dt () X(ω) S(ω) = lim (3) ω S(ω)dω X(ω) : F of x : [X] [ = ] [x t] Power spectral density

More information

RT300/140/105シリーズ 取扱説明書

RT300/140/105シリーズ 取扱説明書 REMOTE & BROADBAND ROUTER RT300i/RT140p/RT140f/RT140i RT140e/RT105p/RT105i/RT105e 2 3 4 5 6 7 8 9 10 Bold face Enter Ctrl Tab BS Del Console RT105i RT300i RT140p RT140f RT140i RT140e RT105p RT105i RT105e

More information