Tài liệu Advanced DSP and Noise reduction P2 pptx
Tài liệu Advanced DSP and Noise reduction P2 pptx
... noise or any wideband noise whose spectrum has a non-flat shape; examples are pink noise, brown noise and autoregressive noise. (e) Impulsive noise: consists of short-duration pulses of random ... Estimation and Modulation Theory. Parts I, II and III. Wiley, New York. 2 NOISE AND DISTORTION 2.1 Introduction 2.6 Thermal Noise 2.2 White Noise 2.7 Shot Noise 2.3 Coloured Noise ... sensation and quality. Figures 2.9(a) and (b) show examples of the spectra of car noise recorded from a BMW and a Volvo respectively. The noise in a car is nonstationary, and varied, and may...
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Tài liệu Advanced DSP and Noise reduction P4 pptx
... Gaussian with mean vector µx and covariance matrix Σxx, and that the noise n(m) is also Gaussian with mean vector µn and covariance matrix Σnn. The signal and noise pdfs model the prior ... two-dimensional signal and noise process, the prior spaces of the signal, the noise, and the noisy signal are illustrated in Figure 4.6. Also illustrated are the likelihood and posterior spaces ... spaceSignal priorspace Noise priorspace Likelihood spaceNoisy signal space Figure 4.6 Sketch of a two-dimensional signal and noise spaces, and the likelihood and posterior spaces of a...
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Tài liệu Advanced DSP and Noise reduction P8 pptx
... ]{}()()()()aXxaXxXaxXaxBBTBBT102121102)(2)()(+)()()()()()(−−−−=+−−−+−−=+=∑∑∑∑−===−=NmPkkPkkNmPPPfbkPmxaPmxkmxamxmbmeE (8.55) where X and x are the signal matrix and vector defined by Equations (8.12) and (8.13), and similarly XB and xB are the signal matrix and vector for the backward ... on the interpolation of a sequence of lost samples, and in Chapters 12 and 13 on the detection and removal of impulsive noise and transient noise pulses. L z–1z–1z–1. . .u(m)x(m ... sub-bands and to model the signal within each sub-band with a linear prediction model as shown in Figure 8.12. The advantages of using a sub-band LP model are as follows: (1) Sub-band linear...
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Tài liệu Advanced DSP and Noise reduction P15 pptx
... the noise power spectrum, PXY(f) is the cross-power spectrum of the channel input and output signals, and H(f) is the frequency response of the channel. Note that in the absence of noise, ... recorders, as illustrated in Figure 15.5, had a bandwidth of about 200 Hz to 4 kHz. However, the limited bandwidth, or even the additive noise or scratch noise pulses, are not considered as the major ... input is a random signal. Standard linear prediction analysis can be viewed as a blind deconvolution method, because both the channel response and the channel input are unknown, and the only...
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Tài liệu Advanced DSP and Noise reduction P1 pdf
... 80 Hz; band 2 is band-pass and covers 80 Hz to 3 kHz; band 3 is high-pass and covers above 3 kHz; and band 4 is also high-pass and covers above 9 kHz. At the encoder the gain of each band is ... time delay, and can be adjusted to coherently combine the signals. The magnitude frequency response of each filter can be used to remove the out–of–band noise. 1.3.8 Dolby Noise Reduction ... have smaller signal–to noise ratio than the low–frequency parts. Therefore noise at high frequencies is more audible and less masked by the signal energy. Dolby noise reduction systems broadly...
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Tài liệu Advanced DSP and Noise reduction P3 pdf
... Autocorrelation and power spectrum of impulsive noise. Impulsive noise is a random, binary-state (“on/off”) sequence of impulses of random amplitudes and random time of occurrence. In Chapter 12, a random ... speech and noise are at least in part random. The concept of randomness is closely associated with the concepts of information and noise. Indeed, much of the work on the processing of random ... impulse, and n(m) is a random noise process. Assuming PXX(f)frxx(m)m Figure 3.6 Autocorrelation and power spectrum of white noise. 62 Probability Models that impulsive noise...
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Tài liệu Advanced DSP and Noise reduction P5 ppt
... signal and the noise HMMs maybe expressed as ()=η,,,maxmaxargnoisesignalsignal noise signalMssYsYssfMAP (5.46) and ()=η,,,maxmaxargnoisesignalnoisesignal noise MssYsYssfMAP ... filtering and the spectral subtraction methods described in Chapters 6 and 11) or by combining the noise and the signal models to model the noisy Signal and Noise Model Combination and Decomposition ... in the presence of noise, since noise causes a mismatch between the clean HMMs and the noisy signals. The noise- induced mismatch can be reduced: either by filtering the noise from the signal...
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Tài liệu Advanced DSP and Noise reduction P6 pdf
... Additive Noise Reduction Consider a signal x(m) observed in a broadband additive noise n(m)., and model as y(m)=x(m)+n(m) (6.45) Assuming that the signal and the noise are ... signal, the noise- free signal and the noise respectively, and rxy is the cross-correlation vector of the noisy signal and the noise- free signal. Substitution of Equations (6.46) and (6.47) ... separability: (a) The signal and noise spectra do not overlap, and the signal can be recovered by a low-pass filter; (b) the signal and noise spectra overlap, and the noise can be reduced but not...
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Tài liệu Advanced DSP and Noise reduction P7 docx
... method, and then consider the computationally inexpensive LMS gradient search method. A z –1wk(m+1)α y(m) e(m)µαw(m) Advanced Digital Signal Processing and Noise Reduction, ... ()[]01|~)1|(ˆ=−−mmmmxxE (7.20) and we have also used the assumption that the signal and the noise are uncorrelated. Substitution of Equations (7.9) and (7.16) in Equation (7.15) yields ... y(m)=x(m)+n(m) (7.34) Let σe2(m) and σn2(m) denote the variances of the excitation signal e(m) and the noise n(m) respectively. Substituting Φ(m+1,m)=a(m) and H(m)=1 in the Kalman filter...
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Tài liệu Advanced DSP and Noise reduction P9 pdf
... vN} span the noise subspace and have σn2 as their eigenvalues. Since the signal and noise eigenvectors are orthogonal, it follows that the signal subspace and the noise subspace are ... matrices of the signal x and the noise as I2Hnσ+=+=SPSRRRnnxxyy (9.93) where Rxx=SPSH and Rnn=σn2I are the autocorrelation matrices of the signal and noise processes, the ... the estimation of sinusoids observed in additive white noise. ejkω0tkω0t T Advanced Digital Signal Processing and Noise Reduction, Second Edition.Saeed V. VaseghiCopyright © 2000...
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