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CONF ON OPTICAL INFORMATION processing SYSTEMS AND architectures 3

作者： PSALTIS, D YONG, Q California Institute of Technology (United States)

ISBN: (纸本)0819406929

In order to implement fully adaptive optical multilayer neural networks, a number of issues involving both learning algorithms and device technologies need to be addressed. In this paper, we present some important modifications to existing learning algorithms that serve to simplify optical architectures and allow the use of simple optical devices.

关键词： Neurons Neural networks Detection and tracking algorithms Optical signal processing Sensors Adaptive optics Evolutionary algorithms Optical components signal detection Spatial light modulators

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Practical Considerations for Acoustic Source Localization in the IoT Era: Platforms, Energy Efficiency, and Performance

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IEEE INTERNET OF THINGS JOURNAL 2019年第3期6卷 5068-5079页

作者： Belloch, Jose A. Badia, Jose M. Igual, Francisco D. Cobos, Maximo Univ Carlos III Madrid Dept Tecnol Elect Leganes 28911 Spain Univ Jaume 1 Dept Ingn & Ciencia Comp Castellon De La Plana 12071 Spain Univ Complutense Madrid Dept Arquitectura Comp & Automat E-28040 Madrid Spain Univ Valencia Comp Sci Dept Valencia Spain

The rapid development of the Internet of Things (IoT) has posed important changes in the way emerging acoustic signal processing applications are conceived. While traditional acoustic processing applications have been developed taking into account high-throughput computing platforms equipped with expensive multichannel audio interfaces, the IoT paradigm is demanding the use of more flexible and energy-efficient systems. In this context, algorithms for source localization and ranging in wireless acoustic sensor networks can be considered an enabling technology for many IoT-based environments, including security, industrial, and health-care applications. This paper is aimed at evaluating important aspects dealing with the practical deployment of IoT systems for acoustic source localization. Recent systems-on-chip composed of low-power multicore processors, combined with a small graphics accelerator (or GPU), yield a notable increment of the computational capacity needed in intensive signal processing algorithms while partially retaining the appealing low power consumption of embedded systems. Different algorithms and implementations over several state-ofthe-art platforms are discussed, analyzing important aspects, such as the tradeoffs between performance, energy efficiency, and exploitation of parallelism by taking into account real-time constraints.

关键词： Acoustic signal processing energy efficiency heterogeneous (hybrid) systems parallel architectures parallel processing source localization wireless acoustic sensor networks (WASNs)

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The sub-optimal receiver structure for the VSB DTV system with an array antenna

The sub-optimal receiver structure for the VSB DTV system wi...

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advanced signal processing algorithms, architectures, and implementations XV

作者： Park, Jaehyun Chun, Joohwan Kim, Ju Yeun Lim, JongSoo Dept. of Electrical Engineering and Computer Science Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Electronics and Telecommunications Research Institute Daejeon Korea Republic of

We look into the optimal structure for the DTV (Digital TV) receiver system with an array antenna. In this paper, we apply the ML(Maximum likelihood) approach, which is a classical method in the theory of detection and estimation. And we examine the limitation of it. It is that the number of multi-paths should be less than that of antennas. But it conflicts with the indoor channel environment. To deal with this problem, we propose a sub-optimal structure, which has lower complexity and computation load, as compared with the optimal structure. And to verify the performance, we compare the SER(symbol error rate) curve of each system by computer simulation.

关键词： signal receivers

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Discrete time processing of linear scale invariant signals and systems

Discrete time processing of linear scale invariant signals a...

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

作者： Izzetoglu, M Onaral, B Chitrapu, P Bilgutay, N Drexel Univ Dept Elect & Comp Engn Philadelphia PA 19104 USA

ISBN: (纸本)0819437611

In this paper, we formulate a framework for discrete-time processing of Linear Scale Invariant (LSI) systems which are invariant to scale changes in time. Continuous-time LSI systems can be processed by Mellin and Modified Scale Transforms analogous to the use of the Laplace and Fourier Transforms in the continuous-time processing of LTI systems. In this work, we present the geometric sampling theorem to prevent aliasing in the scale domain. We also derive the perfect reconstruction filter in time domain, the discrete-time convolution sum, the Discrete Time Modified Scale Transform (DTMST) and the Discrete Modified Scale Transform (DMST) for geometrically sampled signals.

关键词： Transform theory Fourier transforms Convolution Electronic filtering signal processing Statistical analysis Toxic industrial chemicals Biomedical optics Computing systems Telecommunications

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Toward blind removal of unwanted sound from orchestrated music

Toward blind removal of unwanted sound from orchestrated mus...

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

作者： Chang, SY Chun, J Univ Suwon Dept Elect Engn Kyungki do South Korea

ISBN: (纸本)0819437611

The problem addressed in this paper is to removing unwanted sounds from music sound. The sound to be removed could be disturbance such as cough. We shall present some preliminary results on this problem using statistical properties of signals. Our approach consists of three steps. We first estimate the fundamental frequencies and partials given noise-corrupted music sound. This gives us the autoregressive (AR) model of the music sound. Then se filter the noise-corrupted sound using the AR parameters. The filtered signal is then subtracted from the original noise-corrupted signal to get the disturbance. Finally the obtained disturbance is used as reference signal to eliminate the disturbance from the noise-corrupted music signal. Above three steps are carried out in a recursive manner using a sliding window or an infinitely growing window with an appropriate forgetting factor.

关键词： Wiener filter music signal processing interference cancellation

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FPGA-based artificial neural network using CORDIC modules

FPGA-based artificial neural network using CORDIC modules

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

作者： Liddicoat, Albert A. Slivovsky, Lynne A. McLenegan, Tim Heyer, Don Calif Polytech State Univ San Luis Obispo Dept Elect Engn San Luis Obispo CA 93407 USA

ISBN: (纸本)0819463922

Artificial neural networks have been used in applications that require complex procedural algorithms and in systems which lack an analytical mathematic model. By designing a large network of computing nodes based on the artificial neuron model, new solutions can be developed for computational problems in fields such as image processing and speech recognition. Neural networks are inherently parallel since each neuron, or node, acts as an autonomous computational element. Artificial neural networks use a mathematical model for each node that processes information from other nodes in the same region. The information processing entails computing a weighted average computation followed by a nonlinear mathematical transformation. Some typical artificial neural network applications use the exponential function or trigonometric functions for the nonlinear transformation. Various simple artificial neural networks have been implemented using a processor to compute the output for each node sequentially. This approach uses sequential processing and does not take advantage of the parallelism of a complex artificial neural network. In this work a hardware-based approach is investigated for artificial neural network applications. A Field Programmable Gate Arrays (FPGAs) is used to implement an artificial neuron using hardware multipliers, adders and CORDIC functional units. In order to create a large scale artificial neural network, area efficient hardware units such as CORDIC units are needed. High performance and low cost bit serial CORDIC implementations are presented. Finally, the FPGA resources and the performance of a hardware-based artificial neuron are presented.

关键词： computer arithmetic field programmable gate arrays (FPGAs) higher-level functions reconfigurable computing digital signal processing and artificial neural networks

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Design of a color image processing algorithm using on-line arithmetic modules

Design of a color image processing algorithm using on-line a...

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

作者： Sinky, MH Tenca, AF Shantilal, AC Lucchese, L Oregon State Univ Corvallis OR 97331 USA

ISBN: (纸本)0819454974

A new class of nonlinear filters for color image processing was proposed by Lucchese and Mitra. This type of color filter processes the chromatic component of images encoded in the International Commission. on Illumination (CIE) u'v' color space. Images processed by this filter do not show color shifts near edges between regions with different intensities. The filter uses linear convolution operations internally and is effective and efficient for denoising and regularizing color images. Image processing systems are computationally intensive and usually require a large amount of area in order to reach desirable levels of performance. The use off on-line arithmetic can decrease the area of the hardware implementation and still maintain a reasonable throughput. This work presents the design of the color filter as a network of on-line arithmetic modules. The network topology and some detail of each arithmetic module are provided. The final implementation targets FPGAs and it is compared in terms of area against an estimate of a conventional design. The throughput of this solution is capable of supporting real-time processing of common image formats.

关键词： achromatic chromatic convolution DSP DIP FPGA on-line arithmetic RGB SRT division

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Non-linear signal processing using index calculus DBNS arithmetic

Non-linear signal processing using index calculus DBNS arith...

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

作者： Muscedere, R Jullien, GA Dimitrov, VS Miller, WC Univ Windsor VLSI Res Grp Windsor ON N9B 3P4 Canada

ISBN: (纸本)0819437611

This paper discusses the use of a recently introduced index calculus Double-Base Number System (IDBNS) for representing and processing numbers for non-linear digital signal processing;the target application is a digital hearing aid processor. The IDBNS representation uses 2 orthogonal bases (2 and 3) to represent real numbers with arbitrary precision. By restricting the number of digits to one or two, it is possible to efficiently represent the real number using the indices of the bases rather than the distribution of the digits. In this paper we discuss the use of the two-digit form of this representation (2-IDBNS) to efficiently perform arithmetic associated with the non-linear processing required to correct the usual forms of hearing loss in a digital hearing aid. The non-linear processing takes the form of dynamic range compression as a function of frequency band. Currently developed digital hearing instrument processors require large dynamic range representations (20-24 bits) in order to accurately generate the dynamic range compression associated with typical hearing loss. We show that the natural non-linear representation afforded by the IDBNS provides both a more efficient signal representation and a more efficient technique for processing the dynamic range compression. We pay particular attention to a novel technique of converting from a linear binary input directly to the 2-IDBNS representation using an observation of partial cyclic repetition in the indices along with near unity approximants.

关键词： computer arithmetic non-linear number representation double-base number system hearing loss

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Bayesian image deblurring and boundary effects

Bayesian image deblurring and boundary effects

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advanced signal processing algorithms, architectures, and implementations XV

作者： Calvetti, Daniela Somersalo, Erkki Department of Mathematics Center for Modeling Integrated Metabolic Systems Case Western Reserve University Cleveland OH United States Department of Mathematics Helsinki University of Technology Helsinki Finland

We consider the deconvolution problem of estimating an image from a noisy blurred version of it. In particular, we are interested in the boundary effects: since the convolution operator is non-local, the blurred image depend on the scenery outside the field of view. Ignoring this dependency leads to image distortion known as boundary effect. In this article, we consider two different approaches to treat the non-locality. One is to estimate the image extended outside the field of view. The other is to treat the influence of the out of view scenery as boundary clutter. Both approaches are considered from the Bayesian point of view.

关键词： Image processing

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Application of higher-order cepstral techniques in problems of fetal heart signal extraction 6

Application of higher-order cepstral techniques in problems ...

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

作者： SabryRizk, M Zgallai, W Hardiman, P ORiordan, J CITY UNIV LONDON DEPT ELECT ENGNSIGNAL PROC GRPLONDON EC1V 0HBENGLAND

ISBN: (纸本)0819422347

Recently, cepstral analysis based on second order statistics and homomorphic filtering techniques have been used in the adaptive decomposition of overlapping, or otherwise, and noise contaminated ECG complexes of mothers and fetals obtained by a transabdominal surface electrodes connected to a monitoring instrument, an interface card, and a PC. Differential time delays of fetal heart beats measured from a reference point located on the mother complex after transformation to cepstra domains are first obtained and this is followed by fetal heart rate variability computations. Homomorphic filtering in the complex cepstral domain and the subuent transformation to the time domain results in fetal complex recovery. However, three problems have been identified with second-order based cepstral techniques that needed rectification in this paper. These are (1) errors resulting from the phase unwrapping algorithms and leading to fetal complex perturbation, (2) the unavoidable conversion of noise statistics from Gaussianess to non-Gaussianess due to the highly non-linear nature of homomorphic transform does warrant stringent noise cancellation routines, (3) due to the aforementioned problems in (1) and (2), it is difficult to adaptively optimize windows to include all individual fetal complexes in the time domain based on amplitude thresholding routines in the complex cepstral domain (i.e. the task of `zooming' in on weak fetal complexes requires more processing time). The use of third-order based high resolution differential cepstrum technique results in recovery of the delay of the order of 120 milliseconds.

关键词： advanced signal processing techniques non-linear adaptive filtering differential bicepstral applications non-invasive fetal ECG monitoring

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