509 research outputs found
Study of L0-norm constraint normalized subband adaptive filtering algorithm
Limited by fixed step-size and sparsity penalty factor, the conventional
sparsity-aware normalized subband adaptive filtering (NSAF) type algorithms
suffer from trade-off requirements of high filtering accurateness and quicker
convergence behavior. To deal with this problem, this paper proposes variable
step-size L0-norm constraint NSAF algorithms (VSS-L0-NSAFs) for sparse system
identification. We first analyze mean-square-deviation (MSD) statistics
behavior of the L0-NSAF algorithm innovatively in according to a novel
recursion form and arrive at corresponding expressions for the cases that
background noise variance is available and unavailable, where correlation
degree of system input is indicated by scaling parameter r. Based on
derivations, we develop an effective variable step-size scheme through
minimizing the upper bounds of the MSD under some reasonable assumptions and
lemma. To realize performance improvement, an effective reset strategy is
incorporated into presented algorithms to tackle with non-stationary
situations. Finally, numerical simulations corroborate that the proposed
algorithms achieve better performance in terms of estimation accurateness and
tracking capability in comparison with existing related algorithms in sparse
system identification and adaptive echo cancellation circumstances.Comment: 15 pages,15 figure
Wideband data-independent beamforming for subarrays
The desire to operate large antenna arrays for e.g. RADAR applications over a wider frequency range is currently limited by the hardware, which due to weight, cost and size only permits complex multipliers behind each element. In contrast, wideband processing would have to rely on tap delay lines enabling digital filters for every element.As an intermediate step, in this thesis we consider a design where elements are grouped into subarrays, within which elements are still individually controlled by narrowband complex weights, but where each subarray output is given a tap delay line or finite impulse response digital filter for further wideband processing. Firstly, this thesis explores how a tap delay line attached to every subarray can be designed as a delay-and-sum beamformer. This filter is set to realised a fractional delay design based on a windowed sinc function. At the element level, we show that designing a narrowband beam w.r.t. a centre frequency of wideband operation is suboptimal,and suggest an optimisation technique that can yield sufficiently accurate gain over a frequency band of interest for an arbitrary look direction, which however comes at the cost of reduced aperture efficiency, as well as significantly increased sidelobes. We also suggest an adaptive method to enhance the frequency characteristic of a partial wideband array design, by utilising subarrays pointing in different directions in different frequency bands - resolved by means of a filter bank - to adaptively suppress undesired components in the beam patterns of the subarrays. Finally, the thesis proposes a novel array design approach obtained by rotational tiling of subarrays such that the overall array aperture is densely constructed from the same geometric subarray by rotation and translation only. Since the grating lobes of differently oriented subarrays do not necessarily align, an effective grating lobe attenuation w.r.t. the main beam is achieved. Based on a review of findings from geometry,a number of designs are highlight and transformed into numerical examples, and the theoretically expected grating lobe suppression is compared to uniformly spaced arrays.Supported by a number of models and simulations, the thesis thus suggests various numerical and hardware design techniques, mainly the addition of tap-delay-line per subarray and some added processing overhead, that can help to construct a large partial wideband array close in wideband performance to currently existing hardware.The desire to operate large antenna arrays for e.g. RADAR applications over a wider frequency range is currently limited by the hardware, which due to weight, cost and size only permits complex multipliers behind each element. In contrast, wideband processing would have to rely on tap delay lines enabling digital filters for every element.As an intermediate step, in this thesis we consider a design where elements are grouped into subarrays, within which elements are still individually controlled by narrowband complex weights, but where each subarray output is given a tap delay line or finite impulse response digital filter for further wideband processing. Firstly, this thesis explores how a tap delay line attached to every subarray can be designed as a delay-and-sum beamformer. This filter is set to realised a fractional delay design based on a windowed sinc function. At the element level, we show that designing a narrowband beam w.r.t. a centre frequency of wideband operation is suboptimal,and suggest an optimisation technique that can yield sufficiently accurate gain over a frequency band of interest for an arbitrary look direction, which however comes at the cost of reduced aperture efficiency, as well as significantly increased sidelobes. We also suggest an adaptive method to enhance the frequency characteristic of a partial wideband array design, by utilising subarrays pointing in different directions in different frequency bands - resolved by means of a filter bank - to adaptively suppress undesired components in the beam patterns of the subarrays. Finally, the thesis proposes a novel array design approach obtained by rotational tiling of subarrays such that the overall array aperture is densely constructed from the same geometric subarray by rotation and translation only. Since the grating lobes of differently oriented subarrays do not necessarily align, an effective grating lobe attenuation w.r.t. the main beam is achieved. Based on a review of findings from geometry,a number of designs are highlight and transformed into numerical examples, and the theoretically expected grating lobe suppression is compared to uniformly spaced arrays.Supported by a number of models and simulations, the thesis thus suggests various numerical and hardware design techniques, mainly the addition of tap-delay-line per subarray and some added processing overhead, that can help to construct a large partial wideband array close in wideband performance to currently existing hardware
Speckle Noise Reduction in Medical Ultrasound Images
Ultrasound imaging is an incontestable vital tool for diagnosis, it provides
in non-invasive manner the internal structure of the body to detect eventually
diseases or abnormalities tissues. Unfortunately, the presence of speckle noise
in these images affects edges and fine details which limit the contrast
resolution and make diagnostic more difficult. In this paper, we propose a
denoising approach which combines logarithmic transformation and a non linear
diffusion tensor. Since speckle noise is multiplicative and nonwhite process,
the logarithmic transformation is a reasonable choice to convert
signaldependent or pure multiplicative noise to an additive one. The key idea
from using diffusion tensor is to adapt the flow diffusion towards the local
orientation by applying anisotropic diffusion along the coherent structure
direction of interesting features in the image. To illustrate the effective
performance of our algorithm, we present some experimental results on
synthetically and real echographic images
Fixed-analysis adaptive-synthesis filter banks
Subband/Wavelet filter analysis-synthesis filters are a major component in many compression algorithms. Such compression algorithms have been applied to images, voice, and video. These algorithms have achieved high performance. Typically, the configuration for such compression algorithms involves a bank of analysis filters whose coefficients have been designed in advance to enable high quality reconstruction. The analysis system is then followed by subband quantization and decoding on the synthesis side. Decoding is performed using a corresponding set of synthesis filters and the subbands are merged together. For many years, there has been interest in improving the analysis-synthesis filters in order to achieve better coding quality. Adaptive filter banks have been explored by a number of authors where by the analysis filters and synthesis filters coefficients are changed dynamically in response to the input. A degree of performance improvement has been reported but this approach does require that the analysis system dynamically maintain synchronization with the synthesis system in order to perform reconstruction.
In this thesis, we explore a variant of the adaptive filter bank idea. We will refer to this approach as fixed-analysis adaptive-synthesis filter banks. Unlike the adaptive filter banks proposed previously, there is no analysis synthesis synchronization issue involved. This implies less coder complexity and more coder flexibility. Such an approach can be compatible with existing subband wavelet encoders. The design methodology and a performance analysis are presented.Ph.D.Committee Chair: Smith, Mark J. T.; Committee Co-Chair: Mersereau, Russell M.; Committee Member: Anderson, David; Committee Member: Lanterman, Aaron; Committee Member: Rosen, Gail; Committee Member: Wardi, Yora
A frequency-based BSS technique for speech source separation.
Ngan Lai Yin.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.Includes bibliographical references (leaves 95-100).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Blind Signal Separation (BSS) Methods --- p.4Chapter 1.2 --- Objectives of the Thesis --- p.6Chapter 1.3 --- Thesis Outline --- p.8Chapter 2 --- Blind Adaptive Frequency-Shift (BA-FRESH) Filter --- p.9Chapter 2.1 --- Cyclostationarity Properties --- p.10Chapter 2.2 --- Frequency-Shift (FRESH) Filter --- p.11Chapter 2.3 --- Blind Adaptive FRESH Filter --- p.12Chapter 2.4 --- Reduced-Rank BA-FRESH Filter --- p.14Chapter 2.4.1 --- CSP Method --- p.14Chapter 2.4.2 --- PCA Method --- p.14Chapter 2.4.3 --- Appropriate Choice of Rank --- p.14Chapter 2.5 --- Signal Extraction of Spectrally Overlapped Signals --- p.16Chapter 2.5.1 --- Simulation 1: A Fixed Rank --- p.17Chapter 2.5.2 --- Simulation 2: A Variable Rank --- p.18Chapter 2.6 --- Signal Separation of Speech Signals --- p.20Chapter 2.7 --- Chapter Summary --- p.22Chapter 3 --- Reverberant Environment --- p.23Chapter 3.1 --- Small Room Acoustics Model --- p.23Chapter 3.2 --- Effects of Reverberation to Speech Recognition --- p.27Chapter 3.2.1 --- Short Impulse Response --- p.27Chapter 3.2.2 --- Small Room Impulse Response Modelled by Image Method --- p.32Chapter 3.3 --- Chapter Summary --- p.34Chapter 4 --- Information Theoretic Approach for Signal Separation --- p.35Chapter 4.1 --- Independent Component Analysis (ICA) --- p.35Chapter 4.1.1 --- Kullback-Leibler (K-L) Divergence --- p.37Chapter 4.2 --- Information Maximization (Infomax) --- p.39Chapter 4.2.1 --- Stochastic Gradient Descent and Stability Problem --- p.41Chapter 4.2.2 --- Infomax and ICA --- p.41Chapter 4.2.3 --- Infomax and Maximum Likelihood --- p.42Chapter 4.3 --- Signal Separation by Infomax --- p.43Chapter 4.4 --- Chapter Summary --- p.45Chapter 5 --- Blind Signal Separation (BSS) in Frequency Domain --- p.47Chapter 5.1 --- Convolutive Mixing System --- p.48Chapter 5.2 --- Infomax in Frequency Domain --- p.52Chapter 5.3 --- Adaptation Algorithms --- p.54Chapter 5.3.1 --- Standard Gradient Method --- p.54Chapter 5.3.2 --- Natural Gradient Method --- p.55Chapter 5.3.3 --- Convergence Performance --- p.56Chapter 5.4 --- Subband Adaptation --- p.57Chapter 5.5 --- Energy Weighting --- p.59Chapter 5.6 --- The Permutation Problem --- p.61Chapter 5.7 --- Performance Evaluation --- p.63Chapter 5.7.1 --- De-reverberation Performance Factor --- p.63Chapter 5.7.2 --- De-Noise Performance Factor --- p.63Chapter 5.7.3 --- Spectral Signal-to-noise Ratio (SNR) --- p.65Chapter 5.8 --- Chapter Summary --- p.65Chapter 6 --- Simulation Results and Performance Analysis --- p.67Chapter 6.1 --- Small Room Acoustics Modelled by Image Method --- p.67Chapter 6.2 --- Signal Sources --- p.68Chapter 6.2.1 --- Cantonese Speech --- p.69Chapter 6.2.2 --- Noise --- p.69Chapter 6.3 --- De-Noise and De-Reverberation Performance Analysis --- p.69Chapter 6.3.1 --- Speech and White Noise --- p.73Chapter 6.3.2 --- Speech and Voice Babble Noise --- p.76Chapter 6.3.3 --- Two Female Speeches --- p.79Chapter 6.4 --- Recognition Accuracy Performance Analysis --- p.83Chapter 6.4.1 --- Speech and White Noise --- p.83Chapter 6.4.2 --- Speech and Voice Babble Noise --- p.84Chapter 6.4.3 --- Two Cantonese Speeches --- p.85Chapter 6.5 --- Chapter Summary --- p.87Chapter 7 --- Conclusions and Suggestions for Future Research --- p.88Chapter 7.1 --- Conclusions --- p.88Chapter 7.2 --- Suggestions for Future Research --- p.91Appendices --- p.92A The Proof of Stability Conditions for Stochastic Gradient De- scent Algorithm (Ref. (4.15)) --- p.92Bibliography --- p.9
Discrete Wavelet Transforms
The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications
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Research and developments of Dirac video codec
This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel University.In digital video compression, apart from storage, successful transmission of the compressed video
data over the bandwidth limited erroneous channels is another important issue. To enable a video
codec for broadcasting application, it is required to implement the corresponding coding tools (e.g.
error-resilient coding, rate control etc.). They are normally non-normative parts of a video codec and
hence their specifications are not defined in the standard. In Dirac as well, the original codec is
optimized for storage purpose only and so, several non-normative part of the encoding tools are still
required in order to be able to use in other types of application.
Being the "Research and Developments of the Dirac Video Codec" as the research title, phase I of
the project is mainly focused on the error-resilient transmission over a noisy channel. The error-resilient
coding method used here is a simple and low complex coding scheme which provides the
error-resilient transmission of the compressed video bitstream of Dirac video encoder over the packet
erasure wired network. The scheme combines source and channel coding approach where error-resilient
source coding is achieved by data partitioning in the wavelet transformed domain and
channel coding is achieved through the application of either Rate-Compatible Punctured
Convolutional (RCPC) Code or Turbo Code (TC) using un-equal error protection between header plus
MV and data. The scheme is designed mainly for the packet-erasure channel, i.e. targeted for the
Internet broadcasting application.
But, for a bandwidth limited channel, it is still required to limit the amount of bits generated from
the encoder depending on the available bandwidth in addition to the error-resilient coding. So, in the
2nd phase of the project, a rate control algorithm is presented. The algorithm is based upon the Quality
Factor (QF) optimization method where QF of the encoded video is adaptively changing in order to
achieve average bitrate which is constant over each Group of Picture (GOP). A relation between the
bitrate, R and the QF, which is called Rate-QF (R-QF) model is derived in order to estimate the
optimum QF of the current encoding frame for a given target bitrate, R.
In some applications like video conferencing, real-time encoding and decoding with minimum
delay is crucial, but, the ability to do real-time encoding/decoding is largely determined by the
complexity of the encoder/decoder. As we all know that motion estimation process inside the encoder
is the most time consuming stage. So, reducing the complexity of the motion estimation stage will
certainly give one step closer to the real-time application. So, as a partial contribution toward realtime
application, in the final phase of the research, a fast Motion Estimation (ME) strategy is designed
and implemented. It is the combination of modified adaptive search plus semi-hierarchical way of
motion estimation. The same strategy was implemented in both Dirac and H.264 in order to
investigate its performance on different codecs. Together with this fast ME strategy, a method which
is called partial cost function calculation in order to further reduce down the computational load of the
cost function calculation was presented. The calculation is based upon the pre-defined set of patterns
which were chosen in such a way that they have as much maximum coverage as possible over the
whole block.
In summary, this research work has contributed to the error-resilient transmission of compressed
bitstreams of Dirac video encoder over a bandwidth limited error prone channel. In addition to this,
the final phase of the research has partially contributed toward the real-time application of the Dirac
video codec by implementing a fast motion estimation strategy together with partial cost function
calculation idea.BBC R&D and Brunel University
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