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Conference on advanced signal processing - algorithms, architectures, and implementations VII

作者： Crouse, MS Nowak, RD Mhirsi, K Baraniuk, RG Rice Univ. (United States) Michigan State Univ. (United States)

ISBN: (纸本)0819425842

This paper addresses the problem of detection and classification of complicated signals in noise. Classical detection methods such as energy detectors and linear discriminant analysis do not perform well in many situations of practical interest. We introduce a new approach based on hidden Markov modeling in the wavelet domain. Using training data, we fit a hidden Markov model (HMM) to the wavelet transform to concisely represent its probabilistic time-frequency structure. The HMM provides a natural framework for performing likelihood ratio tests used in signal detection and classification. We compare our approach with classical methods for classification of nonlinear processes, change-point detection, and detection with unknown delay.

关键词： wavelets hidden Markov models detection classification

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Exhaustive scheduling and retiming of digital signal processing systems

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-ANALOG AND DIGITAL signal processing 1998年第7期45卷 821-838页

作者： Denk, TC Parhi, KK Lucent Technol Bell Labs Holmdel NJ 07733 USA Univ Minnesota Dept Elect & Comp Engn Minneapolis MN 55455 USA

Scheduling and retiming are important techniques used in the design of hardware and software implementations of digital signal processing algorithms. In this paper, techniques are developed for generating all scheduling and retiming solutions for a strongly connected data-flow graph, allowing a designer to explore the space of possible implementations. Formulations are developed for two scheduling problems. The first scheduling problem assumes a bit-parallel target architecture. The formulation for this problem is general because it considers retiming the dataflow graph as part of scheduling, and this formulation reduces to the retiming formulation as a special case. The second scheduling problem assumes a bit-serial target architecture. Based on these formulations, the conditions for a legal scheduling solution are derived, and a systematic technique is presented for exhaustively generating all legal scheduling solutions for a strongly connected data-flow graph. Since retiming is a special case of scheduling, this systematic technique can also be used for exhaustively generating all legal retiming solutions. A technique is also developed for exhaustively generating only those bit-parallel schedules which satisfy a given set of resource constraints, The techniques for exhaustively generating scheduling and retiming solutions are demonstrated for several filters. For example, we show that a simple filter such as the biquad has 224 possible retiming solutions for a latency of one time unit. We also show that a fifth-order wave digital elliptic filter has 4.7 million and 580 million scheduling solutions for iteration periods of 17 and 18, respectively.

关键词： data flow graphs high-level synthesis parallel architectures retiming scheduling signal processing very large scale integration

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Time-frequency decomposition based on information

Time-frequency decomposition based on information

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Conference on advanced signal processing algorithms, architectures, and implementations xvI

作者： Aviyente, Selin Michigan State Univ E Lansing MI 48824 USA

ISBN: (纸本)0819463922

In array processing applications, it is desirable to extract the sources that generate the observed signals. There are various source separation and component extraction algorithms in literature including principal component analysis (PCA) and independent component analysis (ICA). However, most of these methods are not designed to deal with time-varying signals and thus are formulated in the time domain. In this paper, we introduce a new time-frequency based decomposition method using an information measure as the decomposition criteria. It is shown that under the assumption of disjoint source signals on the time-frequency plane, this method can extract the sources up to a scalar factor. Based on the QR decomposition of the mixing matrix, the source extraction algorithm is reduced to finding the optimal N-dimensional rotation of the observed time-frequency distributions. The proposed algorithm is implemented using the steepest descent approach to find the optimal rotation angle. The performance of the method is illustrated for example signals and compared to some well-known decomposition techniques.

关键词： Time-frequency analysis Independent component analysis Transform theory Principal component analysis Associative arrays Image information entropy Matrices signal processing Sensors Array processing

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Architecture for real time wood inspection

Architecture for real time wood inspection

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Conference on advanced signal processing algorithms, architectures, and implementations X

作者： Malasne, N Paindavoine, M Lab Elect & Informat Image F-21078 Dijon France

This study has been realized to improve industrial machines that allow to analyze planks by detecting their width and too important defects thanks to a computer vision system. These machines are currently piloted by s... 详细信息

ISBN: (纸本)0819437611

关键词： real time processing defects detection FPGA

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Modern microphone array for hearing aid and speech processing 6

Modern microphone array for hearing aid and speech processin...

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Conference on advanced signal processing algorithms, architectures, and implementations VI

作者： Wang, A Yao, K Hudson, RE Korompis, D Lorenzelli, F Soli, SD Gao, S UNIV CALIF LOS ANGELES DEPT ELECT ENGNLOS ANGELESCA 90095

ISBN: (纸本)0819422347

For various audio, teleconference, hearing aid, and voice recognition applications, a microphone array is known to be an effective method to enhance the SNR in noisy environments resulting in significant improvement of speech intelligibility or recognition. We propose an novel electronically steerable microphone array based on the Maximum Energy concentration criterion to form a focused beam toward the desired speech source, attenuating background noises and rejecting discrete spatial interferers. The design and implementation of a prototype DSP-based microphone array system are described. Some details on microphone measurement, calibration, and optimization needed to achieve a high performance microphone array are discussed. Computer simulated and measured array performances are presented to show the effectiveness of the array system.

关键词： Sensors Calibration signal to noise ratio Digital signal processing Computer simulations Near field Acoustics Computing systems signal processing Speaker recognition

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Analytical approximations of translational subpixel shifts in signal and image registrations

Analytical approximations of translational subpixel shifts i...

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Conference on advanced signal processing algorithms, architectures, and Implementantions xvIII

作者： Zhang, Qiang Wake Forest Univ Hlth Sci Biostat Sci Dept Winston Salem NC 27157 USA

ISBN: (纸本)9780819472946

Analytical approximations of translational subpixel shifts in both signal and image registrations are derived by setting the derivatives of a normalized cross correlation function to zero and solving them. Without the need of iterative searching, this methods achieves a complexity of only O(mn), given an image size of m x n. Without the need to upsample, computation memory is also saved. Tests using simulated signals and images show good results.

关键词： Subpixel image registration image superresolution

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advanced Baseband processing algorithms, Circuits, and implementations for 5G Communication

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IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS 2017年第4期7卷 477-490页

作者： Zhang, Chuan Huang, Yuan-Hao Sheikh, Farhana Wang, Zhongfeng Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Jiangsu Peoples R China Natl Tsing Hua Univ Dept Elect Engn Hsinchu 30013 Taiwan Natl Tsing Hua Univ Inst Commun Engn Hsinchu 30013 Taiwan Intel Corp Circuit Res Lab Intel Labs Hillsboro OR 97124 USA Nanjing Univ Sch Elect Sci & Engn Nanjing 210046 Jiangsu Peoples R China

The rapid emergence of 5G communications technology and standardization has seen an accelerated transfer of theoretical concepts to advanced development and implementation. Not only are 5G baseband signal processing algorithms becoming more important, but also the co-design and implementation of corresponding circuits, architectures, and platforms are becoming necessary due to rapid standardization of 5G communications. This timely overview paper introduces circuits and systems (CAS) for key enabling technologies for the new 5G era: massive MIMO, mmWave baseband systems, NOMA schemes, advanced channel coding, and so on. The state-of-the-art research progress in these areas is summarized for interested readers to initiate discussion on limitations of existing solutions and open research problems that are looking for innovative solutions, especially in the CAS area. We hope this paper can bridge the gap between the theoretical investigation and application implementation for 5G communications.

关键词： 5G baseband implementations massive MIMO mmWave precoder non-orthogonal multiple-access (NOMA) schemes channel decoders

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Comparison of time-frequency signal analysis techniques with application to speech recognition

Comparison of time-frequency signal analysis techniques with...

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advanced signal processing algorithms, architectures, and implementations III

作者： Reilly, Andrew P. Boashash, Boualem Queensland Univ. of Technology Brisbane Queensland Australia

ISBN: (纸本)081940943X

Techniques for machine recognition of speech exist, but use representations of the speech signal which cannot convey some of the speech information. Alternatives from time-frequency and time-scale analysis are compared with the traditional methods with a view to improving the word recognition rate. Experiments have shown the speech recognition rate improves in some cases.

关键词： Speech recognition

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Image processing and low discrepancy sequences

Image processing and low discrepancy sequences

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Conference on advanced signal processing algorithms, architectures, and implementations IX

作者： Nair, D Wenzel, L Natl Instruments Austin TX 78727 USA

ISBN: (纸本)0819432938

It is well known that high-dimensional integrals can be solved with Monte Carlo algorithms. Recently, it was discovered that there is a relationship between low discrepancy sets and the efficient evaluation of higher-dimensional integrals. Theory suggests that for midsize dimensional problems, algorithms based on low discrepancy sets should out perform all other existing methods by an order of magnitude in terms of the number of sample points used to evaluate the integrals. We show that the field of image processing can potentially take advantage of specific properties of low discrepancy sets. To illustrate this, we applied the theory of low discrepancy sequences to some relatively simple image processing and computer vision related operations such as the estimation of gray level image statistics, fast location of objects in a binary image and the reconstruction of images from a sparse set of points. Our experiments show that compared to standard methods, the proposed new algorithms are faster and statistically more robust. Classical low discrepancy sets based on the Halton and Sobol' sequences were investigated thoroughly and showed promising results. The use of low discrepancy sequences in image processing for image characterization, understanding and object recognition is a novel and promising area for further investigation.

关键词： sampling random sampling low-discrepancy sequences image statistics image reconstruction

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Spatial polarimetric time-frequency distributions and applications to direction-of-arrival estimation

Spatial polarimetric time-frequency distributions and applic...

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Conference on advanced signal processing algorithms architectures and implementations XIII

作者： Zhang, YM Amin, MG Obeidat, BA Villanova Univ Ctr Adv Commun Villanova PA 19085 USA

ISBN: (纸本)0819450782

Time-frequency distributions (TFDs) have evolved to be a powerful technique for nonstationary signal analysis and synthesis. With the use of a multi-sensor array, spatial time-frequency distributions (STFDs) have been developed and successfully applied to high-resolution direction-of-arrival (DOA) estimation and blind recovery of the source waveforms. In this paper, the polarimetric dimension is introduced to the STFDs resulting in the spatial polarimetric time-frequency distributions (SPTFDs) as a platform for the processing of non-stationary polarized signals. In the SPTFD platform, polarized signals are decomposed (projected) into two orthogonal polarization components, such as horizontal and vertical, and later processed in a manner where their polarization characteristics are exploited. This empowers the STFDs with additional degrees of freedom and improves the robustness of the signal and noise subspaces, and therefore, serving to enhance DOA estimation, signal recovery, and source separation performance. To demonstrate the advantages of the SPTFDs, the polarimetric time-frequency MUSIC (PTF-MUSIC) method for DOA estimation is proposed based on the SPTFD platform and is shown to outperform the time-frequency, polarimetric, and conventional MUSIC methods.

关键词： time-frequency distributions array signal processing polarization smart antennas MUSIC

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