The Experts below are selected from a list of 234 Experts worldwide ranked by ideXlab platform

Gwohwa Ju - One of the best experts on this subject based on the ideXlab platform.

  • INTERSPEECH - Improved speech enhancement by applying time-Shift Property of DFT on hankel matrices for signal subspace decomposition.
    2020
    Co-Authors: Gwohwa Ju
    Abstract:

    In previous studies, the signal subspace technique for speech enhancement was extended and a perceptually constrained generalized singular value decomposition (PCGSVD)-based algorithm [1] was developed which properly integrated the auditory masking effect and the GSVD algorithm. Both objective measures and subjective tests verified that this approach can offer better performance than the GSVD-based approach and the conventional spectral subtraction (SS) algorithm. But very high computational complexity is required in the PCGSVD-based method when performing the matrices decomposition via the GSVD algoruthm. In this paper, we properly utilize the time-Shift Property of DFT and the special structure of Hankel matrices to perform similar functions previously offered by GSVD, and a perceptually constrained minimum variance estimation algorithm is developed. By replacing GSVD algorithm with DFT, the computation complexity is significantly reduced, almost the same as the conventional SS algorithm. Experiments showed that comparable performance to that of the PCGSVD-based approach can be achieved, regardless of whether the additive noise is stationary or not, specially when it is non-white.

  • improved speech enhancement by applying time Shift Property of dft on hankel matrices for signal subspace decomposition
    Conference of the International Speech Communication Association, 2004
    Co-Authors: Gwohwa Ju
    Abstract:

    In previous studies, the signal subspace technique for speech enhancement was extended and a perceptually constrained generalized singular value decomposition (PCGSVD)-based algorithm [1] was developed which properly integrated the auditory masking effect and the GSVD algorithm. Both objective measures and subjective tests verified that this approach can offer better performance than the GSVD-based approach and the conventional spectral subtraction (SS) algorithm. But very high computational complexity is required in the PCGSVD-based method when performing the matrices decomposition via the GSVD algoruthm. In this paper, we properly utilize the time-Shift Property of DFT and the special structure of Hankel matrices to perform similar functions previously offered by GSVD, and a perceptually constrained minimum variance estimation algorithm is developed. By replacing GSVD algorithm with DFT, the computation complexity is significantly reduced, almost the same as the conventional SS algorithm. Experiments showed that comparable performance to that of the PCGSVD-based approach can be achieved, regardless of whether the additive noise is stationary or not, specially when it is non-white.

R Rost - One of the best experts on this subject based on the ideXlab platform.

  • application and correction of the exponential window for frequency response functions
    Mechanical Systems and Signal Processing, 1997
    Co-Authors: W Fladung, R Rost
    Abstract:

    Abstract Applying windows to experimental data is a common practice in modal testing to minimise the effects of leakage, and the exponential window is used for the transient signals measured with impact testing and burst random excitation. Used properly, the exponential can minimise leakage errors on lightly damped signals and can also improve the signal-to-noise of heavily damped signals. The time constant of the exponential window is specified typically by the user, and this paper discusses guidelines for specifying the window for both types of response signal. The effect of the exponential window is to increase the apparent damping of the measured system, and the correction for this effect on the estimated modal parameters is developed by utilising the Shift Property of the Laplace transform. In addition, the transfer function of a half-period sine pulse, which is a representative model of an impact force signal, is studied to show the need for, and consequences of, applying the exponential window to both the force signal and response signals. Finally, several numerical simulation test cases of sdof system as presented to demonstrate the issues discussed in preceding sections.

Jafar Saniie - One of the best experts on this subject based on the ideXlab platform.

  • Processing algorithms for three-dimensional data compression of ultrasonic radio frequency signals
    IET Signal Processing, 2015
    Co-Authors: Pramod Govindan, Jafar Saniie
    Abstract:

    © The Institution of Engineering and Technology 2015.Ultrasonic systems are widely used in imaging applications for non-destructive evaluation, quality assurance and medical diagnosis. These applications require large volumes of data to be processed, stored and/or transmitted in real-time. Therefore it is essential to compress the acquired ultrasonic radio frequency (RF) signal without inadvertently degrading desirable signal features. In this paper, two algorithms for ultrasonic signal compression are analysed based on: sub-band elimination using discrete wavelet transform; and decimation/interpolation using time-Shift Property of Fourier transform. Both algorithms offer high signal reconstruction quality with a peak signal-to-noise ratio (PSNR) between 36 to 39 dB for minimum 80% compression. The computational loads and signal reconstruction quality are examined in order to determine the best compression method in terms of the choice of DWT kernel, sub-band decomposition architecture and computational efficiency. Furthermore, for compressing a large amount of volumetric information, three-dimensional (3D) compression algorithms are designed by utilising the temporal and spatial correlation properties of the ultrasonic RF signals. The performance analysis indicates that the 3D compression algorithm presented in this paper offers an overall 3D compression ratio of 95% with a minimum PSNR of 27 dB.

  • Processing algorithms for three-dimensional data compression of ultrasonic radio frequency signals
    IET Signal Processing, 2015
    Co-Authors: Pramod Govindan, Jafar Saniie
    Abstract:

    Ultrasonic systems are widely used in imaging applications for non-destructive evaluation, quality assurance and medical diagnosis. These applications require large volumes of data to be processed, stored and/or transmitted in real-time. Therefore it is essential to compress the acquired ultrasonic radio frequency (RF) signal without inadvertently degrading desirable signal features. In this paper, two algorithms for ultrasonic signal compression are analysed based on: sub-band elimination using discrete wavelet transform; and decimation/interpolation using time-Shift Property of Fourier transform. Both algorithms offer high signal reconstruction quality with a peak signal-to-noise ratio (PSNR) between 36 to 39 dB for minimum 80% compression. The computational loads and signal reconstruction quality are examined in order to determine the best compression method in terms of the choice of DWT kernel, sub-band decomposition architecture and computational efficiency. Furthermore, for compressing a large amount of volumetric information, three-dimensional (3D) compression algorithms are designed by utilising the temporal and spatial correlation properties of the ultrasonic RF signals. The performance analysis indicates that the 3D compression algorithm presented in this paper offers an overall 3D compression ratio of 95% with a minimum PSNR of 27 dB.

J.s. Baras - One of the best experts on this subject based on the ideXlab platform.

  • Time-recursive architectures and wavelet transform
    1993 IEEE International Conference on Acoustics Speech and Signal Processing, 1993
    Co-Authors: E. Frantzeskakis, J.s. Baras
    Abstract:

    The time-recursive computation has been proved as a particularly useful tool in real-time data compression and in transform domain adaptive filtering, with applications in the areas of audio, radio, sonar, and video. An architectural framework for parallel time-recursive computation is proposed. The authors consider a class of linear operators that consists of the discrete time, time invariant, compactly supported, but otherwise arbitrary kernel functions. They define a Shift Property of the linear operators and reveal its relation with the time-recursive implementation. The potential of the proposed framework is demonstrated by designing a time-recursive architecture for the discrete wavelet transform.

Chung-li Wang - One of the best experts on this subject based on the ideXlab platform.

  • ICNC - Exploiting the Shift Property of structured LDPC codes for reduced-complexity sliced message passing based decoder design
    2012 International Conference on Computing Networking and Communications (ICNC), 2012
    Co-Authors: Xiaoheng Chen, Chung-li Wang
    Abstract:

    The sliced message passing (SMP) scheme breaks the sequential tie of CN update and VN update and presents an efficient way of elevating the hardware utilization ratio and increasing throughput. However, the forward and backward permutation networks complicate the message routing and make the SMP-based decoder not amenable for codes with large CN degrees. By utilizing the Shift Property in some structured codes, we reduced the permutation network by almost 59% when compared with the state-of-art designs. Overall, this design technique will make SMP-based decoder more cost-efficient and applicable for the future communications and storage systems.

  • Exploiting the Shift Property of structured LDPC codes for reduced-complexity sliced message passing based decoder design
    2012 International Conference on Computing Networking and Communications (ICNC), 2012
    Co-Authors: Xiaoheng Chen, Chung-li Wang
    Abstract:

    The sliced message passing (SMP) scheme breaks the sequential tie of CN update and VN update and presents an efficient way of elevating the hardware utilization ratio and increasing throughput. However, the forward and backward permutation networks complicate the message routing and make the SMP-based decoder not amenable for codes with large CN degrees. By utilizing the Shift Property in some structured codes, we reduced the permutation network by almost 59% when compared with the state-of-art designs. Overall, this design technique will make SMP-based decoder more cost-efficient and applicable for the future communications and storage systems.