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A multi-beam Scan Mode Synthetic Aperture Radar processor suitable for satellite operation

A multi-beam Scan Mode Synthetic Aperture Radar processor su...

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International conference on Application Specific Systems (ASAP), architectures and Processors

作者： Mohammad Reza Mohammadnia Lesley Shannon School of Engineering Science Simon Fraser University Burnaby British Columbia Canada

ISBN: (纸本)9781509015047

As FPGA device sizes increase, they offer greater opportunities for on-site data processing, which is potentially useful for reducing the transmission requirements for applications with large data sets. For satellite applications, unlike ASICs, designers also benefit from an FPGA's ability to be reprogrammed to update functionality over the lifetime of a satellite (15+ years) and a mission (often 5+ years), while having significantly lower power costs than GPGPUs or high performance processors. This paper presents the first custom, fully pipelined, adaptable framework for multi-beam Scan Mode Synthetic Aperture Radar (SAR), the only 24/7 remote sensing imaging system that is capable of producing high-resolution global images in any weather conditions. As high resolution SAR or even low-resolution global-coverage generates on the order of hundreds of Megabytes of raw data per second, onboard SAR processing would reduce this transmitted data by orders of magnitude. Our Scan-mode SAR processor is scalable to different bit-widths and frame-sizes. We are able to process 81×730 frames of 8-bit I-Q channels from each scan (1.4 MB) in less than 1.5 ms, approximately 102 times faster than a corresponding estimated C solution leveraging the Intel Integrated Performance Primitives, and 150 times faster than the corresponding fully vectorized software solution run in MATLAB (6-core, 3.5 Ghz CPU).

关键词： Synthetic aperture radar image coding Field programmable gate arrays Azimuth Algorithm design and analysis Radar imaging

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Nano-engineered architectures for ultra-low power wireless body sensor nodes

Nano-engineered architectures for ultra-low power wireless b...

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International conference on Hardware/Software Codesign and System Synthesis (CODES)

作者： Rubén Braojos David Atienza Mohamed M. Sabry Aly Tony F. Wu H.-S. Philip Wong Subhasish Mitra Giovanni Ansaloni École Polytechnique Fédérale de Lausanne Switzerland Stanford University Stanford CA US Stanford University CA U.S.A Università della Svizzera Italiana Switzerland

ISBN: (纸本)9781509035908

Wireless body sensor nodes (WBSNs) are miniaturized devices that are able to acquire, process and transmit bio-signals (such as electrocardiograms, respiration or human-body kinetics). WBSNs face major design challenges due to extremely limited power budgets and very small form factors. We demonstrate, for the first time in the literature, the use of disruptive nanotechnologies to create new nano-engineered ultra-low power (ULP) WBSN architectures. Compared to state-of-the-art multi-core WBSN designs, our new architectures dramatically reduce power consumption by 5.42× and footprint by 5×, while fulfilling real-time processing requirements of bio-signal monitoring applications. Our WBSN architectures achieve these results by utilizing emerging non-volatile memory technologies (such as resistive RAM and spin-transfer torque RAM) and their ultra-dense and fine-grained three-dimensional integration with logic (such as monolithic three-dimensional integration naturally enabled by carbon nanotube field-effect transistors).

关键词： Computer architecture Nonvolatile memory Three-dimensional displays CNTFETs Random access memory Silicon

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An optimized fast codeword search algorithm for vector quantization

An optimized fast codeword search algorithm for vector quant...

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Iranian conference on Electrical Engineering (ICEE)

作者： Mobin Jamali Vahid Ghafarinia Mohammad Ali Montazeri Department of Electrical and Computer Engineering Isfahan university of Technology Isfahan IRAN

ISBN: (纸本)9781467387903

Vector quantization is a popular data compression method with a widespread use in signal processing and pattern recognition applications. However its computational demand is increased tremendously as the size of date set and the dimension of samples grow larger. Here we have proposed a new fast-search algorithm to enhance the computational cost and the execution time of the conventional VQ method. This algorithm relies on the Chebyshev distance for distortion measurement and Triangular Inequality Elimination (TIE) for codeword elimination. The proposed algorithm was employed for the recognition of isolated spoken Persian digits. Results show that this algorithm can remarkably reduce the number of calculations while its encoding error is closed to the full search algorithm.

关键词： Distortion Chebyshev approximation image coding Algorithm design and analysis signal processing algorithms Distortion measurement Encoding

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A frequency co-channel adaptive algorithm for speech quality enhancement

A frequency co-channel adaptive algorithm for speech quality...

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International conference on Engineering & MIS (ICEMIS)

作者： Mohamed Djendi Sara Bensafia Meriem Safi University of Blida 1 Signal Processing and Image Laboratory (LATSI) Blida Algeria

ISBN: (纸本)9781509055807

In this paper, we propose a new transform domain implementation of the backward blind source separation (BBSS) structure combined with the normalized least mean square NLMS algorithm. The proposed algorithm uses the short time Fourier transform to get best performances in the frequency domain in comparison with its time domain version. The performance improvements of the proposed frequency-domain BBSS (FD-BBSS) algorithm are low complexity and fast convergence speed properties. In order to see well the performance of the proposed FD-BBSS algorithm, we compare its performances with other competitive algorithms and we use objective criteria to evaluate their behavior in speech enhancement application when very noisy observations are available.

关键词： Speech Speech enhancement Frequency-domain analysis signal processing algorithms Noise measurement Adaptive filters Algorithm design and analysis

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Flexible FPGA-Based architectures for Curve Point Multiplication over GF(p)

Flexible FPGA-Based Architectures for Curve Point Multiplica...

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Euromicro Symposium on Digital System design

作者： Dorian Amiet Andreas Curiger Paul Zbinden HSR Hochschule für Technik IMES Institut für Mikroelektronik und Embedded Systems Rapperswil Switzerland Securosys SA Zürich Switzerland

Elliptic curve cryptography (ECC) is widely used as an efficient mechanism to secure private data using public-key protocols. This paper focuses on ECC over prime fields (GF(p)). We present a novel hardware architecture that calculates the elliptic curve point multiplication (ECPM). Our processor supports arbitrary prime fields with sizes up to 1024 bits. Different standards, which use curves in short Weierstrass form are supported. A Xilinx Virtex-7 implementation of the proposed hardware architecture takes from 0.69 ms for a 192-bit point multiplication up to 9.7 ms for 512-bit. The implementation takes only 20 DSP slices and 6816 LUTs. To the authors knowledge, this is the best performance reported so far for ECC point multiplication for arbitrary prime field curves without the use of FPGA reconfiguration.

关键词： Computer architecture Elliptic curve cryptography Hardware Clocks Digital signal processing Elliptic curves Pipelines

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WiFi indoor localization based on K-means

WiFi indoor localization based on K-means

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International conference on Audio, Language and image processing, ICALIP

作者： Yazhou Zhong Fei Wu Juan Zhang Bo Dong Shanghai Key Laboratory of Computer Software Evaluating & Testing Shanghai China Shanghai University of Engineering Science School of Electronic and Electrical Engineering Shanghai China Shanghai University of Engineering Science Shanghai CN

ISBN: (纸本)9781509006557

A large number of studies show that in complex indoor propagation environment, parameters of indoor positioning method for typical applications, such as localization performance of TOA, TDOA, AOA, RSSI method is often less than ideal. In order to reduce the influence of indoor environmental factors on the indoor wireless positioning, improve the positioning accuracy and expand the location area, the indoor wireless positioning method based on WiFi K-means is proposed. The improved distance formula is used to take into account the effect of attribute values, and the difference between different objects can be calculated more accurately. The AP in the position of each room is established by testing the signal strength of different signals. The experimental results show that the precision in location probability of 3 meters is more than 80%, which relative than hard clustering algorithm, positioning accuracy is improved.

关键词： Fingerprint recognition IEEE 802.11 Standard Clustering algorithms Classification algorithms Wireless communication Databases Algorithm design and analysis

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A fully-digital and fully synthetizable TDC for high energy physics experiments

A fully-digital and fully synthetizable TDC for high energy ...

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International conference on Event-based Control, Communication, and signal processing (EBCCSP)

作者： P. Bifulco V. Izzo S. Mastroianni A. Aloisio R. Giordano F. Ameli V. Bocci S. Cadeddu L. Casu A. Lai A. Loi I.N.F.N. Sez. Napoli Napoli Italy I.N.F.N. and Università di Napoli “Federico II” Napoli Italy I.N.F.N. Sez. Roma Roma Italy I.N. wlun F.N. Sez. Cagliari Cagliari Italy

ISBN: (纸本)9781509041978

Trigger and data acquisition systems (TDAQ) of High Energy Physics (HEP) experiments intensively use time measurements for calibration of signals and synchronization between their different elements. Typically, electronics systems for time measurement are designed using a classical mixed-signal approach, while all-digital architectures are nowadays being explored and studied by state-of-art research. Indeed, although an optimized mixed-signal design reaches better performances, it requires a significant amount of design time w.r.t. a fully-digital design. Moreover, an analog IP blocks cannot be easily ported into a new technology, if compared with full digital IPs. In this work, we present a fully-digital TDC application, which is based on a fully synthesizable DCO. The TDC measures the phase relationship between a 40 MHz reference clock and a timing signal under measurement. The DCO design is independent from the technology and it can be described by using a high level Hardware Description Language; moreover, due to its specific characteristics, it can be synthesized, placed and routed by using automatic tools. In this work, we present the architecture of the DCO and of the TDC, their performances and the results on a preliminary implementation on a 130 nm ASIC prototype. The TDC is planned to be used in the upgrade of the Muon detector readout electronic in LHCb experiment at CERN. The TDC presented in this paper has the task of measuring the phase difference between the 40 MHz LHC machine clock and a digital signal coming from the muon detector. One of the main constraints of the TDC is on the phase difference resolution, which has to be about 1.5 ns, in order to cope with to the required resolution of the experiment.

关键词： Phase measurement Histograms Detectors signal resolution Mesons Clocks

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Detecting story-related subject captions in Chinese news videos using spatio-temporal analysis

Detecting story-related subject captions in Chinese news vid...

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IEEE International conference on signal processing, Communications and Computing (ICSPCC)

作者： Xihan Wang Xiaoyi Feng Zhaoqiang Xia Abdenour Hadid Northwestern Polytechnical University School of Electronics and Information Xi'an China Center for Machine Vision and Signal Analysis University of Oulu Finland

ISBN: (纸本)9781509027095

Story-related subject captions (SSCs) are the texts which are added to news videos to summarize the story. Compared to all types of caption texts (channel logo, scene locations, scrolling marquee, time, speaker names, audio subtitles, dates etc.), only SSCs describe the news stories and this is useful in news video analysis and retrieval systems. Different from most existing methods in the literature which mainly focus on detecting all types of caption texts in static images, we propose an efficient approach for detecting story-related subject captions using spatio-temporal analysis. We design various types of spatial and temporal features that are intrinsic to SSCs and robust to different variations. Stroke Width Transform (SWT) is first applied to compute connected components. These components are then clustered into chains with similar geometric properties and colors, yielding in candidate text captions. These candidates are finally refined using spatial and temporal analysis. A new challenging data set with ground truth and evaluation protocol is built and will be made publicly available for research purposes. Our experimental analysis shows that our proposed algorithm yields in promising results which compare favorably against traditional approaches in the literature.

关键词： Videos Feature extraction image edge detection Databases Joining processes image color analysis Protocols

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Gabor filter bank-based GEI features for human Gait recognition

Gabor filter bank-based GEI features for human Gait recognit...

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International conference on Telecommunications and signal processing (TSP)

作者： Ait O. Lishani Larbi Boubchir Emad Khalifa Ahmed Bouridane Department of Computer Science and Digital Technologies Northumbria University Newcastle upon Tyne UK Department of Computer Science University of Paris 8 France

ISBN: (纸本)9781509012893

This paper proposes a supervised feature extraction approach which is capable to select distinctive features for the recognition of human gait under clothing and carrying conditions thus improving the recognition performances. The principle of the suggested approach is based on the use of feature texture descriptors extracted from Gait Energy image (GEI). The proposed features are computed using the bank of Gabor filters and then selected using Spectral Regression Kernel Discriminant Analysis (SRKDA) reduction algorithm. The proposed method is evaluated on CASIA Gait database (dataset B) under variations of clothing and carrying conditions for different viewing angles; and the experimental results using one-against-all SVM classifier have given attractive results of up to 91% in terms of Correct Classification Rate (CCR) when compared to existing and similar state-of-the-art methods.

关键词： Feature extraction Gait recognition Clothing Databases Kernel Algorithm design and analysis

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Multilevel thresholding selection based on chaotic multi-verse optimization for image segmentation

Multilevel thresholding selection based on chaotic multi-ver...

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International Joint conference on Computer Science and Software Engineering (JCSSE)

作者： Tanachapong Wangchamhan Sirapat Chiewchanwattana Khamron Sunat Department of Computer Science Khon Kaen University Khon Kaen Thailand

ISBN: (纸本)9781509020348

Multilevel thresholding is the most important method for image processing. Conventional multilevel thresholding methods have proven to be efficient in bi-level thresholding; however, when extended to multilevel thresholding, they prove to be computationally more costly, as they comprehensively search the optimal thresholds for the objective function. This paper presents a chaotic multi-verse optimizer (CMVO) algorithm using Kapur's objective function in order to determine the optimal multilevel thresholds for image segmentation. The proposed CMVO algorithm was applied to various standard test images, and evaluated by peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). The CMVO algorithm efficiently and accurately searched multilevel thresholds and reduced the required computational times.

关键词： Algorithm design and analysis image segmentation Grippers Optimization Linear programming Nickel Software algorithms

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