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Block truncation signature coding for hyeprspectral analysis

Block truncation signature coding for hyeprspectral analysis

引用

Imaging Spectrometry XIII

作者： Chakravarty, Sumit Chang, Chein-I. Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States

ISBN: (纸本)9780819473066

This paper introduces a new signature coding which is designed based on the well-known Block Truncation Coding (BTC). It comprises of bit-maps of the signature blocks generated by different threshold criteria. Two new BTC-based algorithms are developed for signature coding, to be called Block Truncation Signature Coding (BTSC) and 2-level BTSC (2BTSC). In order to compare the developed BTC based algorithms with current binary signature coding schemes such as Spectral Program Analysis Manager (SPAM) developed by Mazer et al. and Spectral Feature-based Binary Coding (SFBC) by Qian et al, three different thresholding functions, local block mean, local block gradient, local block correlation are derived to improve the BTSC performance where the combined bit-maps generated by these thresholds can provide better spectral signature characterization. Experimental results reveal that the new BTC-based signature coding performs more effectively in characterizing spectral variations than currently available binary signature coding methods.

关键词： Managers

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A cepstral domain algorithm for formant frequency estimation from noise-corrupted speech

A cepstral domain algorithm for formant frequency estimation...

引用

International Conference on Neural Networks and signal processing

作者： S. A. Fattah W.-P. Zhu M. O. Ahmad Centre for Signal Processing and Communications DepartmentElectrical and Computer Engineering Concordia University Montreal QUE Canada

ISBN: (纸本)9781424423101

A new scheme for the estimation of formant frequencies from noise-corrupted speech signals is presented in this paper. In order to overcome the effect of noise, first, instead of conventional autocorrelation function (ACF), a once-repeated ACF of the observed data is employed. A ramp cosine cepstrum model of the ORACF of speech signal is developed, followed by a model-fitting based least-square optimization to extract the formants. For the purpose of implementation, the discrete cosine transform (DCT) is used which offers computational advantages for real signals and solves the phase unwrapping problem. Synthetic and natural vowels as well as some naturally spoken sentences in noisy environments are tested. The experimental results demonstrate a better performance obtained by the proposed scheme in comparison to some of the existing methods at low levels of signal-to-noise ratio.

关键词： signal to noise ratio Speech Estimation Discrete cosine transforms Frequency estimation Noise Noise measurement

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A closed-form semi-blind solution to MIMO-OFDM channel estimation

A closed-form semi-blind solution to MIMO-OFDM channel estim...

引用

International Conference on Neural Networks and signal processing

作者： Feng Wan Wei-Ping Zhu M.N.S. Swamy Centre for Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

ISBN: (纸本)9781424423101

Semi-blind channel estimation as a combination of the training-based or pilot-assisted method and a pure blind approach is considered to be a feasible solution for practical wireless systems due to its better estimation accuracy as well as spectral efficiency. However, in the existing semi-blind channel estimation techniques, the weighting factor employed to trade off the training-based and the blind criteria has not been appropriately determined. In this paper, a closed-form solution is developed for semi-blind channel estimation of MIMO-OFDM systems. An appealing scheme for the computation of the weighting factor is proposed, leading to an analytical expression for the weighting factor in terms the MSE (mean square error) of the training-based criterion and that of the blind part. A number of computer simulation-based experiments are conducted, confirming the effectiveness of the derived semi-blind solution.

关键词： Channel estimation OFDM MIMO Estimation Receiving antennas signal processing Training

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A Temporal Matching Method for Pitch Determination from Noisy Speech signals

A Temporal Matching Method for Pitch Determination from Nois...

引用

51st Midwest Symposium on Circuits and Systems (MWSCAS 2008), vol.2

作者： C. Shahnaz W. P. Zhu M. O. Ahmad Centre for Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

A new method based on temporal matching is presented in this paper for pitch determination from noisy speech signals. At first, a variable-length average magnitude sum function (VLAMSF) that exhibits a periodicity similar to the pitch period of the voiced speech, has been proposed. We argue that the Discrete Cosine Transform (DCT) power spectrum of the VLAMSF is capable of revealing an estimate of a pitch-harmonic (PH) more accurately even in a heavy noisy scenario. Then, exploiting the extracted PH, we formulate an impulse train with a variable-period that is used to temporally match the periodicity of the proposed VLAMSF for pitch determination. It has been shown through extensive simulations using the Keele database that our new approach consistently outperforms the other existing methods especially at low signal-to-noise ratios (SNRs).

关键词： Speech Noise measurement Discrete cosine transforms signal to noise ratio Speech processing Harmonic analysis Databases

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An algorithm for the identification of autoregressive moving average systems from noisy observations

An algorithm for the identification of autoregressive moving...

引用

Canadian Conference on electrical and computer engineering (CCECE)

作者： S. A. Fattah W.-P. Zhu M. O. Ahmad Centre for Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

This paper presents an algorithm for the parameter estimation of minimum-phase autoregressive moving average (ARMA) systems from noise-corrupted observations. In order to estimate the AR parameters of the ARMA system, an enhanced autocorrelation function (ACF) of the observed data is employed in a modified form of least-squares Yule-Walker equations. For the estimation of the MA parameters, first, a noise-subtraction algorithm is proposed to reduce the effect of noise from the residual signal which is obtained by filtering the noisy ARMA signal via the estimated AR parameters. The MA parameters are then estimated by using the spectral factorization corresponding to the noise-compensated residual signal. computer simulations are carried out for ARMA systems of different orders and simulation results demonstrate a superior identification performance in terms of estimation accuracy and consistency under noisy conditions.

关键词： Working environment noise Parameter estimation signal processing algorithms Equations Noise reduction signal processing Autocorrelation computer simulation Autoregressive processes System identification

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A method for pitch estimation from noisy speech signals based on a pitch-harmonic extraction

A method for pitch estimation from noisy speech signals base...

引用

International Conference on Neural Networks and signal processing

作者： C. Shahnaz W. -P. Zhu M. O. Ahmad Centre for Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

ISBN: (纸本)9781424423101

A new method for pitch estimation from noisy speech signals based on a pitch-harmonic extraction is presented in this paper. At first, a variable-length average magnitude difference function (VLAMDF) that is able to alleviate the adverse effects of intrinsic falling minima of the conventional AMDF, has been proposed. We argue that the fast Fourier transform (FFT) power spectrum of the VLAMDF is capable of revealing an estimate of a pitch-harmonic (PH) more accurately even in a heavy noisy scenario. Then, exploiting the extracted PH, a two-fold criterion is developed in the FFT domain to acquire the corresponding harmonic number for the determination of the pitch. The superior efficacy of the proposed pitch estimator relative to some of the existing ones is confirmed through simulation results using the Keele database.

关键词： Pitch estimation coordinated mining Voice signal Noise Fast Fourier transform Speech PH signals PITCHES pitch

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Identification of autoregressive moving average systems from noise-corrupted observations

Identification of autoregressive moving average systems from...

引用

Annual IEEE Northeast Workshop on Circuits and Systems (NEWCAS)

作者： S. A. Fattah W.-P. Zhu M. O. Ahmad Centre for Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

In this paper, a new scheme for the identification of minimum-phase autoregressive moving average (ARMA) systems from noise-corrupted observations is presented. Analyzing the characteristics of the autocorrelation function (ACF) of the observed data in the presence of noise, a set of equations has been developed which is capable of estimating the AR parameters of the ARMA system as well as the noise variance. In order to estimate the MA parameters, first, a residual signal is obtained by filtering the noisy observations via the estimated AR parameters. Utilizing the estimated noise variance and the AR parameters, a noise-subtraction algorithm is proposed to reduce the effect of noise from the ACF of the residual signal. The MA parameters are then estimated employing the spectral factorization corresponding to the noise-compensated ACF of the residual signal. computer simulations on different ARMA systems demonstrate a superior identification results in terms of estimation accuracy and consistency even under a heavy noisy condition.

关键词： Noise Estimation Noise measurement Accuracy Correlation signal to noise ratio System identification

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On extracting pitch from noisy speech signals based on spectral and temporal enhancement

On extracting pitch from noisy speech signals based on spect...

引用

Annual IEEE Northeast Workshop on Circuits and Systems (NEWCAS)

作者： C. Shahnaz W. -P. Zhu M. O. Ahmad Centre for Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

A new pitch extractor based on spectral and temporal enhancement of noisy speech signals is presented in this paper. A discrete cosine transform based modified power spectral subtraction scheme is developed and employed prior to pitch extraction in order to suppress the underlying non-stationary noise. The de-noised speech thus obtained is then passed through an inverse filter, whose parameters are derived from the linear prediction (LP) analysis, yielding an output referred to as the LP residual. Since the LP residual is capable of delivering the knowledge of Glottal Closure instants, exploiting its high correlation property, an average magnitude sum function as well as an average magnitude difference function are introduced. The periodicity property of both the functions is argued to be integrated and an enhanced temporal function is put forward for robust pitch extraction in a multi-talker babble noise scenario. The superior efficacy of the proposed pitch extractor relative to some of the existing ones is confirmed through simulation results using the Keele database.

关键词： Speech Noise Discrete cosine transforms Noise measurement signal to noise ratio Speech enhancement Databases

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An Algorithm for ARMA Model Parameter Estimation from Noisy Observations

An Algorithm for ARMA Model Parameter Estimation from Noisy ...

引用

2008 IEEE International Symposium on Circuits and Systems (ISCAS 2008), vol.9

作者： S. A. Fattah W.-P. Zhu M. O. Ahmad Centre for Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

This paper presents a new algorithm for the parameter estimation of minimum-phase autoregressive moving average (ARMA) systems from noise-corrupted observations. In order to estimate the AR parameters of the ARMA system, based on a repeated autocorrelation function (ACF) of the observed data, a set of zero lag compensated equations has been developed. For the estimation of the MA parameters, first, a noise-subtraction algorithm is proposed to reduce the effect of noise from the ACF of the residual signal which is obtained by filtering the noisy ARMA signal via the estimated AR parameters. The MA parameters are then estimated by using a spectral factorization corresponding to the noise-compensated ACF of the residual signal. computer simulations are carried out for ARMA systems of different orders under noisy environments and simulation results demonstrate a superior identification performance in terms of estimation accuracy and consistency.

关键词： Parameter estimation Working environment noise signal processing algorithms Noise reduction Autoregressive processes Autocorrelation Equations signal processing computer simulation Filters

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A pitch extraction algorithm in noise based on temporal and spectral representations

A pitch extraction algorithm in noise based on temporal and ...

引用

International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： C. Shahnaz W. -P. Zhu M. O. Ahmad Centre for Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

In this paper, a new algorithm for pitch extraction from noisy speech signals based on both temporal and spectral representations is presented. We derive a harmonic sinusoidal correlation (HSC) model of clean speech as a temporal representation. Given only a noisy speech frame, a noise-robust least-squares minimization technique is proposed to acquire the parameters of the HSC model which are directly employed for the accurate estimation of a pitch-harmonic (PH). Exploiting the extracted PH and based on a spectral representation which is an enhanced spectrum in the discrete cosine transform domain, a two-fold criterion is developed in order to achieve the true consecutive number corresponding to PH that is finally adopted for pitch detection in the presence of noise. Simulation results using the Keele pitch extraction reference database manifest that combining the multi cues obtained from the temporal as well as spectral representations, the proposed algorithm is able to achieve a superior efficacy in comparison to some of the existing methods from high to very low signal-to-noise ratio (SNR) levels.

关键词： Speech enhancement signal processing algorithms Speech processing Discrete cosine transforms signal to noise ratio Noise robustness Power harmonic filters Autocorrelation White noise Speech analysis

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