pp d 2 * Hz Hz 3 10 db Wind-induced noise, Noise reduction, Microphone array, Beamforming 1
|
|
- ゆきひら つねざき
- 5 years ago
- Views:
Transcription
1 pp d 2 * Hz Hz 3 10 db Wind-induced noise, Noise reduction, Microphone array, Beamforming PSS [1] [2 4] 2 Wind-induced noise reduction using a small twochannel microphone array, by Naoto Sakata, Tetsuro Murakami, Hirofumi Nakajima and Kazuhiro Nakadai Naoto Sakata@clarion. co.jp SN 1.2 [5] [6] 2 Crosswind Downwind 1 exp( 7x) exp( 3.2x) x λ d x = d/λ λ = v/f v m/s f [7] [2] 2 [3] 3 [4] [2 4]
2 cm Crosswind Downwind d mm v m/s IC khz 30 s 3 TCM (a) 4mm AV-LEADER TCM-370 2(b) L R L R AV-LEADER TCM NEOVE FTS30-T12 IC TASCAM DR-05 CELESTRON CE γ(a l (ω),b l (ω)) γ(a l (ω),b l (ω))= A l (ω)b l(ω) A l (ω) 2 B l (ω) 2 (1) A l (ω) B l (ω) ω l = 1, 2,...,L A l (ω) A l (ω) l = L l=1 A l(ω)/la l (ω) A l (ω) γ c (ω) γ c (ω) =γ(x 1,l (ω),x 2,l (ω)) (2) X 1,l (ω) X 2,l (ω) 1, 2
3 L 2 R X 1,l (ω) X 1,l (ω) = N 1 n=0 x 1 (n + Sl)w(n)e jωn/f s (3) j w(n) x 1 (n) 1 n N FFT S f s X 2,l (ω) x 2 (n) N =2 12 S = N/2 w(n) γ a (ω) γ a (ω) =γ(g( X 1,l (ω) ),G( X 2,l (ω) )) (4) G(A s,l (ω)) A s,l (ω) l 0 G(A s,l (ω)) = A s,l (ω) A s,l (ω) s γ p (ω) γ p (ω) =γ(g( X 1,l (ω) 2 ),G( X 2,l (ω) 2 )) (5) v =2.2m/s Downwind d =10mm 3 γ c (ω) 125 Hz Hz PSS 1 8kHz 6 v =2.2m/s Downwind 10 mm v =2.2m/s d =10mm Downwind [6] 8 d =10mm Downwind
4 n h(n) q(n) k(n) (6) 9 Y (ω) =X(ω)H(ω)+Q(ω)K(ω) (7) 1 4kHz v =1.1m/s 9 v =2.2m/s d =10mm Downwind Hz 50 Hz Hz x(n) y(n) y(n) =x(n) h(n)+q(n) k(n) (6) (6) (7) 4.2 L R l(n) r(n) l m (n) r m (n) l m (n) r m (n) w(n) FFT L m (ω) R m (ω) L m (ω) L m (ω) = FFT{l m (n)w(n),n} (8) N FFT{x(n),N} x(n) N FFT R m (ω) L m (ω) L m (ω) R m (ω) G L (ω) G R (ω) Z m (ω) Z m (ω) =G L (ω)l m (ω)+g R (ω)r m (ω) (9) G L (ω) G R (ω) G L (ω) G R (ω) IFFT G L (ω) G R (ω) g L (ω) g R (ω) g L (n) = IFFT {G L (ω),n} (10) g R (n) = IFFT {G R (ω),n} (11) IFFT {X(ω),N} X(ω) N g L (n) g R (n) l(n) r(n) z(n) =g L (n) l(n)+g R (n) r(n) (12)
5 2 743 z(n) 12 G L (ω) =1 G R (ω) LS-BF SS-BF LS-BF G L (ω) =1 0 G R (ω) L m (ω) R m (ω) L(ω) R(ω) (7) L(ω) =Q(ω)K L (ω) (13) R(ω) =Q(ω)K R (ω) (14) K L (ω) K R (ω) L R (9) (13) (14) Z(ω) Z(ω) =1 Q(ω)K L (ω)+g R (ω)q(ω)k R (ω) (15) Z(ω) =0 G R (ω) G R (ω) G R (ω) = K L(ω) (16) K R (ω) 4.4 SS-BF L R K L (ω) K R (ω) H L (ω) H R (ω) L(ω) R(ω) L(ω) R(ω) (7) L(ω) =X(ω)H L (ω)+q(ω)k L (ω) (17) R(ω) =X(ω)H R (ω)+q(ω)k R (ω) (18) (9) Z(ω) Z(ω) = X(ω)(G L (ω)h L (ω)+g R (ω)h R (ω)) +Q(ω)(G L (ω)k L (ω)+g R (ω)k R (ω)) (19) L X(ω)H L (ω) R Q(ω)K R (ω) Z(ω) ( = X(ω)H L (ω) G L (ω)+g R (ω) H ) R(ω) H L (ω) ( +Q(ω)K R (ω) G L (ω) K ) L(ω) K R (ω) + G R(ω) (20) 0 G L (ω) G R (ω) (20) G L (ω) G R (ω) G L (ω)+g R (ω) H R(ω) H L (ω) = 1 (21) G L (ω) K L(ω) K R (ω) + G R(ω) = 0 (22) H R (ω)/h L (ω)=h LR (ω) K L (ω)/k R (ω)=k RL (ω) (21) (22) 1 G L (ω) = K RL (ω)h LR (ω) 1 K RL (ω) G R (ω) = K RL (ω)h LR (ω) 1 (23) (24) H LR (ω) L R K RL (ω) R L 4.5 LS-BF SS-BF PSS [1] SN [8] D2 DAS-KJ191 AD/DA M-Audio Fast Track Pro PC Lenovo ThinkPad L BOSE 101-MM 12 YAMAHA MX-1 RWC [9] No khz
6 K RL (ω) =e jωt u (26) cm Downwind d mm v m/s 44.1 khz 10 s BOSE 101-MM H LR (ω) K RL(ω) H LR (ω) K RL(ω) H LR (ω) =e jωt s (25) t s L R t u R L t s 340 m/s d t u 2 φ(ω) φ(ω) φ(ω) =unwrap{arg {γ c (ω)}} (27) arg{} unwrap{} ˆτ J(τ) τ J(τ) τ φ(ω) ( ωτ) 2 ˆτ J(τ) P J(τ) = φ(ω p ) ( ω p τ) 2 (28) p=1 ω p p P φ(ω) ( ωτ) φ(ω) ( ωτ) ˆτ ˆτ = ω + φ (29) ω 0 ω P φ ω (φ = φ(ω)) ω + ω L R H LR (ω) TSP Time-Stretched Pulse TSP 10 H L (ω) H R (ω) TSP H L (ω) H R (ω) H LR (ω) H R (ω)h L (ω) H LR (ω) = H L (ω) 2 +max ( H L (ω) 2) r h (30) r h
7 K RL (ω) R L L m (ω) R m (ω) L m (ω) R m (ω) ω L ω R ω ω R L K RL (ω) L ω L ω = K RL (ω)r ω (31) R ω R + ω K RL (ω) K RL (ω) =R + ω L ω (32) K RL (ω) K RL (ω)r m (ω) L m (ω) (23) (24) SS-BF K RL (ω α )H LR (ω α )=1 ω = ω α SS-BF d(ω) G L (ω) = d(ω) 2 +max ( d(ω) 2) (33) r g G R (ω) = K RL (ω)d(ω) d(ω) 2 +max ( d(ω) 2) r g (34) r g d(ω) d(ω) =H LR (ω)k RL (ω) 1 (35) SN x(n) P x (ω) x(n) x m (n) (8) X m (ω) P x (ω) = 1 M X m (ω) 2 (36) M m=1 M f 1 f 2 SN f 1 f 2 ω p p 1 p 2 ω p1 =2πf 1 ω p2 =2πf 2 SNR(p 1,p 2 ) =10log 10 ( p2 p=p 1 P s (ω p ) p2 p=p 1 {P s+n (ω p ) P s (ω p )} ) (37) P s (ω) P s+n (ω) 37 p2 p=p 1 {P s+n (ω p ) P s (ω p )} 0 SNR(p 1,p 2 )=0 [8] κ ratio κ ori κ proc κ κ = M P Cmp 4 m=1 p=1 MP ( M P Cmp 2 m=1 p=1 MP ) 2 (38) C mp m p M P (8) 2 (38) κ ori κ proc κ ratio κ ratio = κ proc κ ori (39) κ ratio κ ori κ proc m/s 2,048 1,024 FFT PSS r h =10 4 r g =10 2 Downwind t s =0 t u = Crosswind t s = t u =0 SN 0 22,050 Hz
8 Hz ,000 Hz 3 PSS 20 PSS Cr Crosswind Original L PSS 500 Hz 8dB 1,000 Hz Original PSS LS-BF Original SS-BF 500 Hz 15 db 1,000 8,000 Hz 14 Dw Downwind PSS Cr LS-BF SS-BF 50 1,000 Hz Original 5dB 3 SN SN LS-BF SS-BF PSS SN LS-BF SN SS-BF Cr 13 db SN PSS Hz 6dB Cr SS-BF SN PSS 6dB Cr Dw 3 SN LS-BF SS-BF PSS Cr 0 22,050 Hz 2.7 db 12.9 db 6.4 db Cr Hz 2.8 db 13.3 db 6.5 db Cr ,000 Hz 2.5 db 3.3 db 1.8 db Dw 0 22,050 Hz 0.8 db 1.6 db 7.7 db Dw Hz 0.8 db 1.5 db 7.8 db Dw ,000 Hz 1.8 db 1.1 db 1.8 db 15 Cr Cr 250 1,000 Hz LS-BF SS-BF LS-BF 125 Hz 5dB 2,000 4,000 Hz 10 db SS-BF 250 Hz 3dB 16 Dw
9 LS-BF SS-BF PSS Cr Cr Dw Dw Dw 4 SN LS-BF SS-BF PSS Cr 0 22,050 Hz 2.9 db 2.3 db 6.4 db Cr Hz 3.1 db 2.2 db 6.5 db Cr ,000 Hz 0.3 db 0.2 db 1.8 db Dw 0 22,050 Hz 2.2 db 1.0 db 7.7 db Dw Hz 2.3 db 1.1 db 7.8 db Dw ,000 Hz 0.4 db 1.4 db 1.8 db 17 LS-BF 250 1,000 Hz Cr 125 Hz 5dB 2,000 4,000 Hz 10 db SS-BF 62.5 Hz 3dB Hz 3dB 4 SN 0 22,050 Hz Hz Cr Dw LS-BF 3dB SS-BF SN 2dB ,000 Hz SN Dw LS-BF SN ,000 Hz SS-BF 0 22,050 Hz Hz SS-BF SN 2dB ,000 Hz SS-BF SN 1.5 db PSS LS-BF SS-BF 5 PSS Cr 2.09 Dw 4.38 LS-BF SS-BF Cr Dw PSS LS-BF SS-BF PSS Dw v =2.6m/s SN 30 db PSS 19 SS-BF 17 PSS SS-BF 1.06 PSS 3.47 SS-BF
10 PSS [ 5 ] R. Raspet, J. Webster and K. Dillion, Framework for wind noise studies, J. Acoust. Soc. Am., 119, (2006). [ 6 ] F. Shields, Low-frequency wind noise correlation in microphone arrays, J. Acoust. Soc. Am., 117, (2005). [ 7 ] D. Herman, Wind noise rejection apparatus, U. S. Patent, US 8,391,529 B2 (2013). [ 8 ] Y. Uemura, Y. Takahashi, H. Saruwatari, K. Shikano and K. Kondo, Automatic optimization scheme of spectral subtraction based on musical noise assessment via higher-order statistics, Proc. Int. Workshop Acoustic Echo and Noise Control (2008). [ 9 ] M. Goto, H. Hashiguchi, T. Nishimura and R. Oka, RWC music database: Popular, classical, and jazz music databases, Proc. 3rd Int. Conf. Music Information Retrieval (ISMIR 2002 ), pp (2002) SS-BF Hz Hz 3 10 db PSS [ 1 ] S. F. Boll, Suppression of acoustic noise in speech using spectral subtraction, IEEE Trans. Acoust. Speech Signal Process., 27, (1979). [ 2 ] M. Yoshida and T. Oku, Wind noise reduction device, U. S. Patent, US 8,428,275 B2 (2013). [ 3 ] Y. Chung, Rejection of flow noise using a coherence function method, J. Acoust. Soc. Am., 62, (1977). [ 4 ] K. Kumatani, B. Raj, R. Singh and J. McDonough, Microphone array post-filter based on spatially-correlated noise, Proc. Interspeech 2012 (2012) NTT NTT JST ERATO IEEE
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 informationTSP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 informationH(ω) = ( G H (ω)g(ω) ) 1 G H (ω) (6) 2 H 11 (ω) H 1N (ω) H(ω)= (2) H M1 (ω) H MN (ω) [ X(ω)= X 1 (ω) X 2 (ω) X N (ω) ] T (3)
72 12 2016 pp. 777 782 777 * 43.60.Pt; 43.38.Md; 43.60.Sx 1. 1 2 [1 8] Flexible acoustic interface based on 3D sound reproduction. Yosuke Tatekura (Shizuoka University, Hamamatsu, 432 8561) 2. 2.1 3 M
More informationIPSJ SIG Technical Report Vol.2014-MUS-104 No /8/27 F0 1,a) 1,b) 1,c) 2,d) (F0) F0 F0 Graphical User Interface (GUI) F0 1. [1] CD MIDI [2] [3,
F,a),b),c) 2,d) (F) F F Graphical User Interface (GUI) F. [] CD MIDI [2] [3, 4] [5] 2 a) ikemiya@kuis.kyoto-u.ac.jp b) itoyama@kuis.kyoto-u.ac.jp c) yoshii@kuis.kyoto-u.ac.jp d) okuno@aoni.waseda.jp TANDEM-STRAIGHT
More informationIPSJ SIG Technical Report 1, Instrument Separation in Reverberant Environments Using Crystal Microphone Arrays Nobutaka ITO, 1, 2 Yu KITANO, 1
1, 2 1 1 1 Instrument Separation in Reverberant Environments Using Crystal Microphone Arrays Nobutaka ITO, 1, 2 Yu KITANO, 1 Nobutaka ONO 1 and Shigeki SAGAYAMA 1 This paper deals with instrument separation
More information2 DS SS (SS+DS) Fig. 2 Separation algorithm for motorcycle sound by combining DS and SS (SS+DS). 3. [3] DS SS 2 SS+DS 1 1 B SS SS 4. NMF 4. 1 (NMF) Y
a) Separation of Motorcycle Sound by Near Field Microphone Array and Nonnegative Matrix Factorization Chisaki YOSHINAGA, Nonmember, Yosuke TATEKURA a), Member, Kazuaki HAMADA, and Tetsuya KIMURA, Nonmembers
More informationuntitled
MRR Physical Basis( 1.8.4) METEK MRR 1 MRR 1.1 MRR 24GHz FM-CW(frequency module continuous wave) 30 r+ r f+ f 1.2 1 4 MRR 24GHz 1.3 50mW 1 rf- (waveguide) (horn) 60cm ( monostatic radar) (continuous wave)
More informationh(n) x(n) s(n) S (ω) = H(ω)X(ω) (5 1) H(ω) H(ω) = F[h(n)] (5 2) F X(ω) x(n) X(ω) = F[x(n)] (5 3) S (ω) s(n) S (ω) = F[s(n)] (5
1 -- 5 5 2011 2 1940 N. Wiener FFT 5-1 5-2 Norbert Wiener 1894 1912 MIT c 2011 1/(12) 1 -- 5 -- 5 5--1 2008 3 h(n) x(n) s(n) S (ω) = H(ω)X(ω) (5 1) H(ω) H(ω) = F[h(n)] (5 2) F X(ω) x(n) X(ω) = F[x(n)]
More information2013 M
2013 M0110453 2013 : M0110453 20 1 1 1.1............................ 1 1.2.............................. 4 2 5 2.1................................. 6 2.2................................. 8 2.3.................................
More information1 1.1 Excel Excel Excel log 1, log 2, log 3,, log 10 e = ln 10 log cm 1mm 1 10 =0.1mm = f(x) f(x) = n
1 1.1 Excel Excel Excel log 1, log, log,, log e.7188188 ln log 1. 5cm 1mm 1 0.1mm 0.1 4 4 1 4.1 fx) fx) n0 f n) 0) x n n! n + 1 R n+1 x) fx) f0) + f 0) 1! x + f 0)! x + + f n) 0) x n + R n+1 x) n! 1 .
More informationmain.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ホットスポット 1 音リアクションイベント BIC GMM 2 3 BIC GMM HMM 10) SVM 11) 12) 13) Bayesian Information Criterion BIC 14) BIC M = M 1, M 2,,
1 1 2 2 BIC GMM Acoustic Event Detection for Finding Hot Spots in Podcasts Kouhei Sumi, 1 Tatsuya Kawahara, 1 Jun Ogata 2 and Masataka Goto 2 This paper presents a method to detect acoustic events that
More information(1) 1.1
1 1 1.1 1.1.1 1.1 ( ) ( ) ( ) { ( ) ( ) { ( ) ( ) { ( ) ( ) { ( ) ( ) { ( ) ( ) ( ) ( ) ( ) 2 1 1.1.2 (1) 1.1 1.1 3 (2) 1.2 4 1 (3) 1.3 ( ) ( ) (4) 1.1 5 (5) ( ) 1.4 6 1 (6) 1.5 (7) ( ) (8) 1.1 7 1.1.3
More informationc 2009 i
I 2009 c 2009 i 0 1 0.0................................... 1 0.1.............................. 3 0.2.............................. 5 1 7 1.1................................. 7 1.2..............................
More information(1.2) T D = 0 T = D = 30 kn 1.2 (1.4) 2F W = 0 F = W/2 = 300 kn/2 = 150 kn 1.3 (1.9) R = W 1 + W 2 = = 1100 N. (1.9) W 2 b W 1 a = 0
1 1 1.1 1.) T D = T = D = kn 1. 1.4) F W = F = W/ = kn/ = 15 kn 1. 1.9) R = W 1 + W = 6 + 5 = 11 N. 1.9) W b W 1 a = a = W /W 1 )b = 5/6) = 5 cm 1.4 AB AC P 1, P x, y x, y y x 1.4.) P sin 6 + P 1 sin 45
More informationIPSJ-MUS
Vol.29-MUS-81 No.2 29/7/29 1 2 1 ground-truth RWC 22 16 Method for Calculating the Subjective-based Music Similarity Measure Yusuke Hiraga, 1 Yasunori Ohishi 2 and Kazuya Takeda 1 In this paper, we propose
More informationLLG-R8.Nisus.pdf
d M d t = γ M H + α M d M d t M γ [ 1/ ( Oe sec) ] α γ γ = gµ B h g g µ B h / π γ g = γ = 1.76 10 [ 7 1/ ( Oe sec) ] α α = λ γ λ λ λ α γ α α H α = γ H ω ω H α α H K K H K / M 1 1 > 0 α 1 M > 0 γ α γ =
More information1. 4cm 16 cm 4cm 20cm 18 cm L λ(x)=ax [kg/m] A x 4cm A 4cm 12 cm h h Y 0 a G 0.38h a b x r(x) x y = 1 h 0.38h G b h X x r(x) 1 S(x) = πr(x) 2 a,b, h,π
. 4cm 6 cm 4cm cm 8 cm λ()=a [kg/m] A 4cm A 4cm cm h h Y a G.38h a b () y = h.38h G b h X () S() = π() a,b, h,π V = ρ M = ρv G = M h S() 3 d a,b, h 4 G = 5 h a b a b = 6 ω() s v m θ() m v () θ() ω() dθ()
More informationnews
ETL NEWS 1999.9 ETL NEWS 1999.11 Establishment of an Evaluation Technique for Laser Pulse Timing Fluctuations Optoelectronics Division Hidemi Tsuchida e-mail:tsuchida@etl.go.jp A new technique has been
More information, (GPS: Global Positioning Systemg),.,, (LBS: Local Based Services).. GPS,.,. RFID LAN,.,.,.,,,.,..,.,.,,, i
25 Estimation scheme of indoor positioning using difference of times which chirp signals arrive 114348 214 3 6 , (GPS: Global Positioning Systemg),.,, (LBS: Local Based Services).. GPS,.,. RFID LAN,.,.,.,,,.,..,.,.,,,
More information[Ver. 0.2] 1 2 3 4 5 6 7 1 1.1 1.2 1.3 1.4 1.5 1 1.1 1 1.2 1. (elasticity) 2. (plasticity) 3. (strength) 4. 5. (toughness) 6. 1 1.2 1. (elasticity) } 1 1.2 2. (plasticity), 1 1.2 3. (strength) a < b F
More informationAUTOMATIC MEASUREMENTS OF STREAM FLOW USING FLUVIAL ACOUSTIC TOMOGRAPHY SYSTEM Kiyosi KAWANISI, Arata, KANEKO Noriaki GOHDA and Shinya
2010 9 AUTOMATIC MEASUREMENTS OF STREAM FLOW USING FLUVIAL ACOUSTIC TOMOGRAPHY SYSTEM 1 2 3 4 Kiyosi KAWANISI, Arata, KANEKO Noriaki GOHDA and Shinya NIGO 1 739-8527 1-4-1 2 739-8527 1-4-1 3 723-0047 12-2
More information2005 1
2005 1 1 1 2 2 2.1....................................... 2 2.2................................... 5 2.3 VSWR................................. 6 2.4 VSWR 2............................ 7 2.5.......................................
More informationmain.dvi
5 IIR IIR z 5.1 5.1.1 1. 2. IIR(Infinite Impulse Response) FIR(Finite Impulse Response) 3. 4. 5. 5.1.2 IIR FIR 5.1 5.1 5.2 104 5. IIR 5.1 IIR FIR IIR FIR H(z) = a 0 +a 1 z 1 +a 2 z 2 1+b 1 z 1 +b 2 z 2
More informationHz
( ) 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 information10_08.dvi
476 67 10 2011 pp. 476 481 * 43.72.+q 1. MOS Mean Opinion Score ITU-T P.835 [1] [2] [3] Subjective and objective quality evaluation of noisereduced speech. Takeshi Yamada, Shoji Makino and Nobuhiko Kitawaki
More information修士論文
SAW 14 2 M3622 i 1 1 1-1 1 1-2 2 1-3 2 2 3 2-1 3 2-2 5 2-3 7 2-3-1 7 2-3-2 2-3-3 SAW 12 3 13 3-1 13 3-2 14 4 SAW 19 4-1 19 4-2 21 4-2-1 21 4-2-2 22 4-3 24 4-4 35 5 SAW 36 5-1 Wedge 36 5-1-1 SAW 36 5-1-2
More informationMicrosoft Word - CTCWEB講座(4章照査)0419.doc
1912 1914 3 58 16 1 58 2 16 3 4 62 61 4 16 1 16 1914 ( 3) 1955 (30) 1961 (36) 1965 (40) 1970 (45) 1983 (58) 1992 ( 4) 1999 (11) 2004 (16) 2 1 2 3 4 5 6 7 8 9 1 10 2 11 12 13 14 15 16 17 18 19 20 21 22
More information振動工学に基礎
Ky Words. ω. ω.3 osω snω.4 ω snω ω osω.5 .6 ω osω snω.7 ω ω ( sn( ω φ.7 ( ω os( ω φ.8 ω ( ω sn( ω φ.9 ω anφ / ω ω φ ω T ω T s π T π. ω Hz ω. T π π rad/s π ω π T. T ω φ 6. 6. 4. 4... -... -. -4. -4. -6.
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
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 informationUWB a) Accuracy of Relative Distance Measurement with Ultra Wideband System Yuichiro SHIMIZU a) and Yukitoshi SANADA (Ultra Wideband; UWB) UWB GHz DLL
UWB a) Accuracy of Relative Distance Measurement with Ultra Wideband System Yuichiro SHIMIZU a) and Yukitoshi SANADA (Ultra Wideband; UWB) UWB GHz DLL UWB (DLL) UWB DLL 1. UWB FCC (Federal Communications
More information<4D F736F F D B B83578B6594BB2D834A836F815B82D082C88C60202E646F63>
単純適応制御 SAC 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/091961 このサンプルページの内容は, 初版 1 刷発行当時のものです. 1 2 3 4 5 9 10 12 14 15 A B F 6 8 11 13 E 7 C D URL http://www.morikita.co.jp/support
More informationuntitled
C L C L 4.5m 3.0m 10% 25% 50% 90% 75% 50% N N N 90% 90% 10% 10% 100 100 10 10 10% 10% :49kN :17 :17kN CBR CBR CBR 5 3,000 / 3,000 /mm /mm 1.2mm 89dB 190dB 3,000 3,000 /mm 20% 20%
More information空気の屈折率変調を光学的に検出する超指向性マイクロホン
23 2 1M36268 2 2 4 5 6 7 8 13 15 2 21 2 23 2 2 3 32 34 38 38 54 57 62 63 1-1 ( 1) ( 2) 1-1 a ( sinθ ) 2J D ( θ ) = 1 (1-1) kaka sinθ ( 3) 1-2 1 Back face hole Amplifier Diaphragm Equiphase wave surface
More informationmain.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成長機構
j im πmkt jin jim π mkt j q out j q im π mkt jin j j q out out π mkt π mkt dn dt πmkt dn v( ) Rmax bf dt πmkt R v ( J J ), J J, J J + + T T, J J m + Q+ / kt Q / kt + ( Q Q+ )/ ktm l / ktm J / J, l Q Q
More informationPart () () Γ Part ,
Contents a 6 6 6 6 6 6 6 7 7. 8.. 8.. 8.3. 8 Part. 9. 9.. 9.. 3. 3.. 3.. 3 4. 5 4.. 5 4.. 9 4.3. 3 Part. 6 5. () 6 5.. () 7 5.. 9 5.3. Γ 3 6. 3 6.. 3 6.. 3 6.3. 33 Part 3. 34 7. 34 7.. 34 7.. 34 8. 35
More informationLT 低コスト、シャットダウン機能付き デュアルおよびトリプル300MHz 電流帰還アンプ
µ µ LT1398/LT1399 V IN A R G 00Ω CHANNEL A SELECT EN A R F 3Ω B C 97.6Ω CABLE V IN B R G 00Ω EN B R F 3Ω 97.6Ω V OUT OUTPUT (00mV/DIV) EN C V IN C 97.6Ω R G 00Ω R F 3Ω 1399 TA01 R F = R G = 30Ω f = 30MHz
More information2.2 (a) = 1, M = 9, p i 1 = p i = p i+1 = 0 (b) = 1, M = 9, p i 1 = 0, p i = 1, p i+1 = 1 1: M 2 M 2 w i [j] w i [j] = 1 j= w i w i = (w i [ ],, w i [
RI-002 Encoding-oriented video generation algorithm based on control with high temporal resolution Yukihiro BANDOH, Seishi TAKAMURA, Atsushi SHIMIZU 1 1T / CMOS [1] 4K (4096 2160 /) 900 Hz 50Hz,60Hz 240Hz
More information医系の統計入門第 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. このサンプルページの内容は, 第 2 版 1 刷発行時のものです.
医系の統計入門第 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/009192 このサンプルページの内容は, 第 2 版 1 刷発行時のものです. i 2 t 1. 2. 3 2 3. 6 4. 7 5. n 2 ν 6. 2 7. 2003 ii 2 2013 10 iii 1987
More information訂正目次.PDF
1 1-1.SAW SAW 1 SAW RF IF SAW GHz SAW v 0 1-1.SAW SAWSurface Acoustic Wave SAW m 100ppm 5 SAW 1-1 IDTInterdigital Transducer IDT f SAW V0 IDT SAW f V0/ 1-2.SAW SAW 10MHz GHz 1.5GHz RF 1.5GHz 130MHz IF
More information) ] [ h m x + y + + V x) φ = Eφ 1) z E = i h t 13) x << 1) N n n= = N N + 1) 14) N n n= = N N + 1)N + 1) 6 15) N n 3 n= = 1 4 N N + 1) 16) N n 4
1. k λ ν ω T v p v g k = π λ ω = πν = π T v p = λν = ω k v g = dω dk 1) ) 3) 4). p = hk = h λ 5) E = hν = hω 6) h = h π 7) h =6.6618 1 34 J sec) hc=197.3 MeV fm = 197.3 kev pm= 197.3 ev nm = 1.97 1 3 ev
More information1. HNS [1] HNS HNS HNS [2] HNS [3] [4] [5] HNS 16ch SNR [6] 1 16ch 1 3 SNR [4] [5] 2. 2 HNS API HNS CS27-HNS [1] (SOA) [7] API Web 2
THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS TECHNICAL REPORT OF IEICE. 657 8531 1 1 E-mail: {soda,matsubara}@ws.cs.kobe-u.ac.jp, {masa-n,shinsuke,shin,yosimoto}@cs.kobe-u.ac.jp,
More information撮 影
DC cathode ray tube, 2.2 log log log + log log / / / A method determining tone conversion characteristics of digital still camera from two pictorial images Tone conversion characteristic Luminance
More informationWISS 2018 [2 4] [5,6] Query-by-Dancing Query-by- Dancing Cao [1] OpenPose 2 Ghias [7] Query by humming Chen [8] Query by rhythm Jang [9] Query-by-tapp
Query-by-Dancing: WISS 2018. Query-by-Dancing Query-by-Dancing 1 OpenPose [1] Copyright is held by the author(s). DJ DJ DJ WISS 2018 [2 4] [5,6] Query-by-Dancing Query-by- Dancing Cao [1] OpenPose 2 Ghias
More informationFormation process of regular satellites on the circumplanetary disk Hidetaka Okada Department of Earth Sciences, Undergraduate school of Scie
Formation process of regular satellites on the circumplanetary disk Hidetaka Okada 22060172 Department of Earth Sciences, Undergraduate school of Science, Hokkaido University Planetary and Space Group
More information2
Rb Rb Rb :10256010 2 3 1 5 1.1....................................... 5 1.2............................................. 5 1.3........................................ 6 2 7 2.1.........................................
More informationx E E E e i ω = t + ikx 0 k λ λ 2π k 2π/λ k ω/v v n v c/n k = nω c c ω/2π λ k 2πn/λ 2π/(λ/n) κ n n κ N n iκ k = Nω c iωt + inωx c iωt + i( n+ iκ ) ωx
x E E E e i ω t + ikx k λ λ π k π/λ k ω/v v n v c/n k nω c c ω/π λ k πn/λ π/(λ/n) κ n n κ N n iκ k Nω c iωt + inωx c iωt + i( n+ iκ ) ωx c κω x c iω ( t nx c) E E e E e E e e κ e ωκx/c e iω(t nx/c) I I
More information1 No.1 5 C 1 I III F 1 F 2 F 1 F 2 2 Φ 2 (t) = Φ 1 (t) Φ 1 (t t). = Φ 1(t) t = ( 1.5e 0.5t 2.4e 4t 2e 10t ) τ < 0 t > τ Φ 2 (t) < 0 lim t Φ 2 (t) = 0
1 No.1 5 C 1 I III F 1 F 2 F 1 F 2 2 Φ 2 (t) = Φ 1 (t) Φ 1 (t t). = Φ 1(t) t = ( 1.5e 0.5t 2.4e 4t 2e 10t ) τ < 0 t > τ Φ 2 (t) < 0 lim t Φ 2 (t) = 0 0 < t < τ I II 0 No.2 2 C x y x y > 0 x 0 x > b a dx
More informationOnsager SOLUTION OF THE EIGENWERT PROBLEM (O-29) V = e H A e H B λ max Z 2 Onsager (O-77) (O-82) (O-83) Kramers-Wannier 1 1 Ons
Onsager 2 9 207.2.7 3 SOLUTION OF THE EIGENWERT PROBLEM O-29 V = e H A e H B λ max Z 2 OnsagerO-77O-82 O-83 2 Kramers-Wannier Onsager * * * * * V self-adjoint V = V /2 V V /2 = V /2 V 2 V /2 = 2 sinh 2H
More informationLD
989935 1 1 3 3 4 4 LD 6 7 10 1 3 13 13 16 0 4 5 30 31 33 33 35 35 37 38 5 40 FFT 40 40 4 4 4 44 47 48 49 51 51 5 53 54 55 56 Abstract [1] HDD (LaserDopplerVibrometer; LDV) [] HDD IC 1 4 LDV LDV He-Ne Acousto-optic
More informationA
A04-164 2008 2 13 1 4 1.1.......................................... 4 1.2..................................... 4 1.3..................................... 4 1.4..................................... 5 2
More information<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 informationuntitled
GeoFem 1 1.1 1 1.2 1 1.3 1 2 2.1 2 2.2 3 2.3 FEM 5 (1) 5 (2) 5 (3) 6 2.4 GeoFem 7 2.5 FEM 16 2.6 19 2.7 26 3.1 33 3.2 35 3.3 GeoFem 36 3.4 48 3.5 49 A A1 A2 A3 A4 A5 A6 A7 GeoFem GeoFem CRS GeoFem GeoFem
More information1 -- 9 -- 3 3--1 LMS NLMS 2009 2 LMS Least Mean Square LMS Normalized LMS NLMS 3--1--1 3 1 AD 3 1 h(n) y(n) d(n) FIR w(n) n = 0, 1,, N 1 N N = 2 3--1-
1 -- 9 3 2009 2 LMS NLMS RLS FIR IIR 3-1 3-2 3-3 3-4 c 2011 1/(13) 1 -- 9 -- 3 3--1 LMS NLMS 2009 2 LMS Least Mean Square LMS Normalized LMS NLMS 3--1--1 3 1 AD 3 1 h(n) y(n) d(n) FIR w(n) n = 0, 1,, N
More informationA Study of Adaptive Array Implimentation for mobile comunication in cellular system GD133
A Study of Adaptive Array Implimentation for mobile comunication in cellular system 15 1 31 01GD133 LSI DSP CMA 10km/s i 1 1 2 LS-CMA 5 2.1 CMA... 5 2.1.1... 5 2.1.2... 7 2.1.3... 10 2.2 LS-CMA... 13 2.2.1...
More informationLMC6022 Low Power CMOS Dual Operational Amplifier (jp)
Low Power CMOS Dual Operational Amplifier Literature Number: JAJS754 CMOS CMOS (100k 5k ) 0.5mW CMOS CMOS LMC6024 100k 5k 120dB 2.5 V/ 40fA Low Power CMOS Dual Operational Amplifier 19910530 33020 23900
More information(interferometer) 1 N *3 2 ω λ k = ω/c = 2π/λ ( ) r E = A 1 e iφ1(r) e iωt + A 2 e iφ2(r) e iωt (1) φ 1 (r), φ 2 (r) r λ 2π 2 I = E 2 = A A 2 2 +
7 1 (Young) *1 *2 (interference) *1 (1802 1804) *2 2 (2005) (1993) 1 (interferometer) 1 N *3 2 ω λ k = ω/c = 2π/λ ( ) r E = A 1 e iφ1(r) e iωt + A 2 e iφ2(r) e iωt (1) φ 1 (r), φ 2 (r) r λ 2π 2 I = E 2
More information12-7 12-7 12-7 12-7 12-8 12-10 12-10 12-10 12-11 12-12 12-12 12-14 12-15 12-17 12-18 10 12-19 12-20 12-20 12-21 12-22 12-22 12-23 12-25 12-26 12-26 12-29 12-30 12-30 12-31 12-33 12-34 12-3 12-35 12-36
More information08-Note2-web
r(t) t r(t) O v(t) = dr(t) dt a(t) = dv(t) dt = d2 r(t) dt 2 r(t), v(t), a(t) t dr(t) dt r(t) =(x(t),y(t),z(t)) = d 2 r(t) dt 2 = ( dx(t) dt ( d 2 x(t) dt 2, dy(t), dz(t) dt dt ), d2 y(t) dt 2, d2 z(t)
More information30
3 ............................................2 2...........................................2....................................2.2...................................2.3..............................
More informationsikepuri.dvi
2009 2 2 2. 2.. F(s) G(s) H(s) G(s) F(s) H(s) F(s),G(s) H(s) : V (s) Z(s)I(s) I(s) Y (s)v (s) Z(s): Y (s): 2: ( ( V V 2 I I 2 ) ( ) ( Z Z 2 Z 2 Z 22 ) ( ) ( Y Y 2 Y 2 Y 22 ( ) ( ) Z Z 2 Y Y 2 : : Z 2 Z
More information8 300 mm 2.50 m/s L/s ( ) 1.13 kg/m MPa 240 C 5.00mm 120 kpa ( ) kg/s c p = 1.02kJ/kgK, R = 287J/kgK kPa, 17.0 C 118 C 870m 3 R = 287J
26 1 22 10 1 2 3 4 5 6 30.0 cm 1.59 kg 110kPa, 42.1 C, 18.0m/s 107kPa c p =1.02kJ/kgK 278J/kgK 30.0 C, 250kPa (c p = 1.02kJ/kgK, R = 287J/kgK) 18.0 C m/s 16.9 C 320kPa 270 m/s C c p = 1.02kJ/kgK, R = 292J/kgK
More information2007-Kanai-paper.dvi
19 Estimation of Sound Source Zone using The Arrival Time Interval 1080351 2008 3 7 S/N 2 2 2 i Abstract Estimation of Sound Source Zone using The Arrival Time Interval Koichiro Kanai The microphone array
More information2014 3
1 3 113 : 1 Copyright c 1 by Kobayashi Keisuke Desktop Music (DTM) DAW (Digital Audio Workstation) YAMAHA Vocaloid DTM MIDI (Musical Instruments Digital Interface) Lee (Non-negative Matrix Factorization;
More informationuntitled
- 37 - - 3 - (a) (b) 1) 15-1 1) LIQCAOka 199Oka 1999 ),3) ) -1-39 - 1) a) b) i) 1) 1 FEM Zhang ) 1 1) - 35 - FEM 9 1 3 ii) () 1 Dr=9% Dr=35% Tatsuoka 19Fukushima and Tatsuoka19 5),) Dr=35% Dr=35% Dr=3%1kPa
More informationIPSJ SIG Technical Report Vol.2012-MUS-94 No.27 Vol.2012-SLP-90 No /2/4 1 2 J K L 3 ( ) GUI Musical Audio Signal Modeling for Joint Estimation
2 J K L 3 GUI Musical Audio Signal Modeling or Joint Estiation o Haronic, Inharonic, and Tibral Structure and its Application to Source Sepatation NAOKI YASURAOKA and HIROSHI G. OKUNO 2 This paper presents
More informationhttp://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 information3-2 PET ( : CYRIC ) ( 0 ) (3-1 ) PET PET [min] 11 C 13 N 15 O 18 F 68 Ga [MeV] [mm] [MeV]
3 PET 3-1 PET 3-1-1 PET PET 1-1 X CT MRI(Magnetic Resonance Imaging) X CT MRI PET 3-1 PET [1] H1 D2 11 C-doxepin 11 C-raclopride PET H1 D2 3-2 PET 0 0 H1 D2 3-1 PET 3-2 PET ( : CYRIC ) ( 0 ) 3-1-2 (3-1
More informationI A A441 : April 21, 2014 Version : Kawahira, Tomoki TA (Kondo, Hirotaka ) Google
I4 - : April, 4 Version :. Kwhir, Tomoki TA (Kondo, Hirotk) Google http://www.mth.ngoy-u.c.jp/~kwhir/courses/4s-biseki.html pdf 4 4 4 4 8 e 5 5 9 etc. 5 6 6 6 9 n etc. 6 6 6 3 6 3 7 7 etc 7 4 7 7 8 5 59
More informationI ( ) 1 de Broglie 1 (de Broglie) p λ k h Planck ( Js) p = h λ = k (1) h 2π : Dirac k B Boltzmann ( J/K) T U = 3 2 k BT
I (008 4 0 de Broglie (de Broglie p λ k h Planck ( 6.63 0 34 Js p = h λ = k ( h π : Dirac k B Boltzmann (.38 0 3 J/K T U = 3 k BT ( = λ m k B T h m = 0.067m 0 m 0 = 9. 0 3 kg GaAs( a T = 300 K 3 fg 07345
More informationd > 2 α B(y) y (5.1) s 2 = c z = x d 1+α dx ln u 1 ] 2u ψ(u) c z y 1 d 2 + α c z y t y y t- s 2 2 s 2 > d > 2 T c y T c y = T t c = T c /T 1 (3.
5 S 2 tot = S 2 T (y, t) + S 2 (y) = const. Z 2 (4.22) σ 2 /4 y = y z y t = T/T 1 2 (3.9) (3.15) s 2 = A(y, t) B(y) (5.1) A(y, t) = x d 1+α dx ln u 1 ] 2u ψ(u), u = x(y + x 2 )/t s 2 T A 3T d S 2 tot S
More informationmain.dvi
BPF 16 2 29 4414 LP F (Low P ass F ilter) HPF(High P ass F ilter) BPF(Band P ass F ilter) ( ) BPF BPF BPF 2 Q BPF 1 BPF BPF BPF 1 8 1 BPF BPF BPF -3[dB] 5[MHz] BPF -3[dB].8[MHz] BPF i 1 1 2 BPF 4 2.1...........................
More informationMicrosoft 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 informationµµ InGaAs/GaAs PIN InGaAs PbS/PbSe InSb InAs/InSb MCT (HgCdTe)
1001 µµ 1.... 2 2.... 7 3.... 9 4. InGaAs/GaAs PIN... 10 5. InGaAs... 17 6. PbS/PbSe... 18 7. InSb... 22 8. InAs/InSb... 23 9. MCT (HgCdTe)... 25 10.... 28 11.... 29 12. (Si)... 30 13.... 33 14.... 37
More informationAN5637
IC SECAM IC SECAM IC 1 SECAM Unit : mm 19.2±0.3 16 9 1 8 (0.71) 0.5±0.1 Seating plane 2.54 1.22±0.25 DIP016-P-0300D 6.2±0.3 5.20±0.25 1.10±0.25 3.05±0.25 7.62±0.25 3 to 15 0.30 +0.10 ) (DIP016- P-0300M)
More information0 s T (s) /CR () v 2 /v v 2 v = T (jω) = + jωcr (2) = + (ωcr) 2 ω v R=Ω C=F (b) db db( ) v 2 20 log 0 [db] (3) v R v C v 2 (a) ω (b) : v o v o =
RC LC RC 5 2 RC 2 2. /sc sl ( ) s = jω j j ω [rad/s] : C L R sc sl R 2.2 T (s) ( T (s) = = /CR ) + scr s + /CR () 0 s T (s) /CR () v 2 /v v 2 v = T (jω) = + jωcr (2) = + (ωcr) 2 ω v R=Ω C=F (b) db db(
More information9 1. (Ti:Al 2 O 3 ) (DCM) (Cr:Al 2 O 3 ) (Cr:BeAl 2 O 4 ) Ĥ0 ψ n (r) ω n Schrödinger Ĥ 0 ψ n (r) = ω n ψ n (r), (1) ω i ψ (r, t) = [Ĥ0 + Ĥint (
9 1. (Ti:Al 2 O 3 ) (DCM) (Cr:Al 2 O 3 ) (Cr:BeAl 2 O 4 ) 2. 2.1 Ĥ ψ n (r) ω n Schrödinger Ĥ ψ n (r) = ω n ψ n (r), (1) ω i ψ (r, t) = [Ĥ + Ĥint (t)] ψ (r, t), (2) Ĥ int (t) = eˆxe cos ωt ˆdE cos ωt, (3)
More information- 1-150 khz18 GHz CATV MATV IEC 60728-2 A B (ITE) 2 (3) 4.1 (1) 3 (CISPR) 1 (CISPR 16-1-1 2.1 2006) (CISPR 16-1-2 1 2003 12004) (CISPR 16-1-3 2.0 2004) (CISPR 16-1-4 2.0 2007) 30 MHz 1000 MHz (CISPR 16-1-5
More informationOPA134/2134/4134('98.03)
OPA OPA OPA OPA OPA OPA OPA OPA OPA TM µ Ω ± ± ± ± + OPA OPA OPA Offset Trim Offset Trim Out A V+ Out A Out D In +In V+ Output In A +In A A B Out B In B In A +In A A D In D +In D V NC V +In B V+ V +In
More informationI A A441 : April 15, 2013 Version : 1.1 I Kawahira, Tomoki TA (Shigehiro, Yoshida )
I013 00-1 : April 15, 013 Version : 1.1 I Kawahira, Tomoki TA (Shigehiro, Yoshida) http://www.math.nagoya-u.ac.jp/~kawahira/courses/13s-tenbou.html pdf * 4 15 4 5 13 e πi = 1 5 0 5 7 3 4 6 3 6 10 6 17
More information1 1 1 1-1 1 1-9 1-3 1-1 13-17 -3 6-4 6 3 3-1 35 3-37 3-3 38 4 4-1 39 4- Fe C TEM 41 4-3 C TEM 44 4-4 Fe TEM 46 4-5 5 4-6 5 5 51 6 5 1 1-1 1991 1,1 multiwall nanotube 1993 singlewall nanotube ( 1,) sp 7.4eV
More informationZ: Q: R: C:
0 Z: Q: R: C: 3 4 4 4................................ 4 4.................................. 7 5 3 5...................... 3 5......................... 40 5.3 snz) z)........................... 4 6 46 x
More informationIPSJ-SLP
F0 MFCC 1 2 3 1 1 1 1 MFCCF0 1 86.7% 90.2% A System for Automatic Discrimination between Singing and Speaking Voices on the Basis of Peak Interval of Spectral Change, F0, and MFCC Shimpei Aso, 1 Takeshi
More informationuntitled
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 informationuntitled
ECOH/YG No. 6 556 754 On the Role o Spectral Width and Shape Parameters in Control o Wave Height Distribution Yoshimi GODA and Masanobu KUDAKA -4-6-4 ( -4-6-4 Distributions o individual wave heights approximately
More informationTriple 2:1 High-Speed Video Multiplexer (Rev. C
www.tij.co.jp OPA3875 µ ± +5V µ RGB Channel OPA3875 OPA3875 (Patented) RGB Out SELECT ENABLE RED OUT GREEN OUT BLUE OUT 1 R G B RGB Channel 1 R1 G1 B1 X 1 Off Off Off 5V Channel Select EN OPA875 OPA4872
More informationSample function Re random process Flutter, Galloping, etc. ensemble (mean value) N 1 µ = lim xk( t1) N k = 1 N autocorrelation function N 1 R( t1, t1
Sample function Re random process Flutter, Galloping, etc. ensemble (mean value) µ = lim xk( k = autocorrelation function R( t, t + τ) = lim ( ) ( + τ) xk t xk t k = V p o o R p o, o V S M R realization
More informationuntitled
0 ( L CONTENTS 0 . sin(-x-sinx, (-x(x, sin(90-xx,(90-xsinx sin(80-xsinx,(80-x-x ( sin{90-(ωφ}(ωφ. :n :m.0 m.0 n tn. 0 n.0 tn ω m :n.0n tn n.0 tn.0 m c ω sinω c ω c tnω ecω sin ω ω sin c ω c ω tn c tn ω
More informationuntitled
18 1 2,000,000 2,000,000 2007 2 2 2008 3 31 (1) 6 JCOSSAR 2007pp.57-642007.6. LCC (1) (2) 2 10mm 1020 14 12 10 8 6 4 40,50,60 2 0 1998 27.5 1995 1960 40 1) 2) 3) LCC LCC LCC 1 1) Vol.42No.5pp.29-322004.5.
More informationuntitled
(a) (b) (c) (d) Wunderlich 2.5.1 = = =90 2 1 (hkl) {hkl} [hkl] L tan 2θ = r L nλ = 2dsinθ dhkl ( ) = 1 2 2 2 h k l + + a b c c l=2 l=1 l=0 Polanyi nλ = I sinφ I: B A a 110 B c 110 b b 110 µ a 110
More information( ) : 1997
( ) 2008 2 17 : 1997 CMOS FET AD-DA All Rights Reserved (c) Yoichi OKABE 2000-present. [ HTML ] [ PDF ] [ ] [ Web ] [ ] [ HTML ] [ PDF ] 1 1 4 1.1..................................... 4 1.2..................................
More informationPlastic Package (Note 12) Note 1: ( ) Top View Order Number T or TF See NS Package Number TA11B for Staggered Lead Non-Isolated Package or TF11B for S
Overture 68W ( ) 0.1 (THD N) 20Hz 20kHz 4 68W 8 38W SPiKe (Self Peak Instantaneous Temperature ( Ke)) SOA (Safe Operating Area) SPiKe 2.0 V ( ) 92dB (min) SN 0.03 THD N IMD (SMTPE) 0.004 V CC 28V 4 68W
More information80 4 r ˆρ i (r, t) δ(r x i (t)) (4.1) x i (t) ρ i ˆρ i t = 0 i r 0 t(> 0) j r 0 + r < δ(r 0 x i (0))δ(r 0 + r x j (t)) > (4.2) r r 0 G i j (r, t) dr 0
79 4 4.1 4.1.1 x i (t) x j (t) O O r 0 + r r r 0 x i (0) r 0 x i (0) 4.1 L. van. Hove 1954 space-time correlation function V N 4.1 ρ 0 = N/V i t 80 4 r ˆρ i (r, t) δ(r x i (t)) (4.1) x i (t) ρ i ˆρ i t
More information