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signal processing and Optimization Tools for Conference Review and Session Assignment

IEEE signal processing MAGAZINE 2015年第3期32卷 141-155页

作者： Sidiropoulos, Nicholas D. Tsakonas, Efthymios E. Univ Minnesota Minneapolis MN 55455 USA IEEE Signal Proc Commun & Networking Tech Comm Santa Clara CA USA

Anyone who has served as a technical program committee (TPC) chair for a conference (or program manager for a funding agency) understands that paper (or proposal panel) review assignment is a demanding job that takes a lot of time, and reviewers are rarely satisfied with the end results. This article presents signal processing tools for two critical ?mass assignment? tasks: assigning papers (or proposals) to reviewers in a way that matches reviewing expertise to scientific content while respecting the reviewers? capacity constraints and splitting accepted papers (or submitted proposals) to sessions (panels) while adhering to session (panel) capacity constraints. The basic idea is to use feature vectors to represent papers and reviewers. Features can be key words or phrases (e.g., optimization or sensor networks) or other types of attributes (e.g., timeliness). This viewpoint enables optimal assignment problem formulations that make sense from a scientific and practical point of view. While optimal solutions are hard to compute for a large number of papers and reviewers, high-quality approximate solutions of moderate complexity are developed here using familiar signal processing and optimization tools. These algorithmic solutions easily outperform days of expert manual work as demonstrated in experiments with real conference data.

关键词： Meetings Complexity theory Optimization Publishing signal processing algorithms Approximation methods Approximation algorithms Professional communication

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signal-processing USING IMPLICIT PHASE

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS 1985年第2期32卷 150-159页

作者： MANRY, MT Department of Electrical Engineering University of Texas Arlington Arlington TX USA

A frequency-domain technique is presented for measuring the average location of the energy of, a sequence. Several properties of the measure are listed and proved. A simple time-domain approximation to the measure is derived and an upper bound on the error of approximation is found. The effects of noise on the measure are thoroughly analyzed. The measure can be used to find and remove the linear part of a Fourier transform's phase without any arctangent operations. it can be used to locate individual signal components which overlap in time but which are disjoint in frequency. The measure may be used in the estimation of time delays or time constants. The algorithms described in this paper require no inverse DFT's and, therefore, run twice as fast as algorithms which utilize FFT convolution.

关键词： signal processing Frequency measurement Time measurement signal processing algorithms Energy measurement Time domain analysis Upper bound Noise measurement Phase measurement Delay estimation

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Integrated Sensing and Communication signal processing Based on Compressed Sensing Over Unlicensed Spectrum Bands

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IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING 2024年第5期10卷 1801-1816页

作者： Liu, Haotian Wei, Zhiqing Li, Fengyun Lin, Yuewei Qu, Hanyang Wu, Huici Feng, Zhiyong Beijing Univ Posts & Telecommun Sch Informat & Commun Beijing 100088 Peoples R China Qingdao Univ Sci & Technol Coll Informat Sci & Technol Qingdao 266061 Shandong Peoples R China ChinaMobile Zijin Innovat Inst Wireless Cloud Network R&D Dept Nanjing 210000 Jiangsu Peoples R China

As a promising key technology of 6th generation (6G) mobile communication system, integrated sensing and communication (ISAC) technology aims to make full use of spectrum resources to enable the functional integration of communication and sensing. The ISAC-enabled mobile communication system regularly operate in non-continuous spectrum bands due to crowded licensed frequency bands. However, the conventional sensing algorithms over non-continuous spectrum bands have disadvantages such as reduced peak-to-sidelobe ratio (PSLR) and degraded anti-noise performance. Facing this challenge, we propose a high-precision ISAC signal processing algorithm based on compressed sensing (CS) in this paper. By integrating the resource block group (RBG) configuration information in 5th generation new radio (5G NR) and channel information matrices, we can dynamically and accurately obtain power estimation spectra. Moreover, we employ the fast iterative shrinkage-thresholding algorithm (FISTA) to address the reconstruction problem and utilize K-fold cross validation (KCV) to obtain optimal parameters. Simulation results show that the proposed algorithm has lower sidelobes or even zero sidelobes compared with conventional sensing algorithms. Meanwhile, compared with the improved 2D FFT algorithm and conventional 2D FFT algorithm, the proposed algorithms in this paper have a maximum improvement of 54.66% and 84.36% in range estimation accuracy, and 41.54% and 97.09% in velocity estimation accuracy, respectively.

关键词： Sensors signal processing algorithms OFDM Symbols Time-frequency analysis 5G mobile communication Radar Compressed sensing (CS) integrated sensing and communication (ISAC) machine learning (ML) non-continuous spectrum non-continuous OFDM (NC-OFDM) signal processing unlicensed spectrum bands

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Low-power signal processing system design for wireless applications

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IEEE PERSONAL COMMUNICATIONS 1998年第3期5卷 20-31页

作者： Meng, TH Hung, AC Tsern, EK Gordon, BM Stanford Univ Dept Elect Engn Stanford CA 94305 USA Chromat Res Inc Sunnyvale CA USA Rambus Inc Mountain View CA USA Silicon Real Federal Way WA USA

Our present ability to work with most multimedia data has been confined to a wired environment, requiring both the data source and the receiver to be physically connected to a power supply and a wired communication link. This article describes the design principles applicable to wireless signal processing systems, using a portable video-on-demand system as an example. The discussion will focus on both the algorithm and circuit design techniques developed for implementing a low-power video compression/decompression system at power levels that are two orders of magnitude below existing solutions. This low-power video compression system not only provides a compression efficiency similar to industry standards, but also maintains a high degree of error tolerance to guard against the transmission errors often encountered in wireless communication.

关键词： signal processing signal processing algorithms Video compression Power supplies signal design Video signal processing Circuit synthesis Communication industry Communication standards Wireless communication

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HIDDEN MARKOV MODEL signal-processing IN PRESENCE OF UNKNOWN DETERMINISTIC INTERFERENCES

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 1993年第1期38卷 146-152页

作者： KRISHNAMURTHY, V MOORE, JB CHUNG, SH AUSTRALIAN NATL UNIV DEPT CHEMCANBERRAACT 2601AUSTRALIA

In this note, expectation maximization (EM) algorithms are used to extract discrete-time, finite-state Markov signals imbedded in a mixture of Gaussian white-noise and deterministic signals of known functional form with unknown parameters. We obtain maximum likelihood estimates of the Markov state levels, state estimates, transition probabilities, and also of the parameters of the deterministic signals. Specifically, we consider two important types of deterministic signals: periodic, or almost periodic signals with unknown frequency components, amplitudes, and phases;polynomial drift in the states of the Markov process with the coefficients of the polynomial unknown. The techniques developed here along with the supporting theory appear more elegant and powerful than ad hoc heuristic alternatives. An illustrative biophysical application for extracting ionic channel currents in cell membranes in the presence of white Gaussian noise and alternating current (AC) ''hum'' is included.

关键词： Hidden Markov models signal processing signal processing algorithms State estimation Polynomials Maximum likelihood estimation Parameter estimation Frequency Markov processes Cells (biology)

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signal processing Methods to Interpret Polychlorinated Biphenyls in Airborne Samples

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IEEE ACCESS 2020年 8卷 147738-147755页

作者： McCarthy, Ryan A. Gupta, Ananya Sen Kubicek, Bernice Awad, Andrew M. Martinez, Andres Marek, Rachel F. Hornbuckle, Keri C. Univ Iowa Dept Elect & Comp Engn Iowa City IA 52242 USA Univ Iowa Iowa Technol Inst ITI Iowa City IA 52242 USA Univ Iowa Dept Civil & Environm Engn Iowa City IA 52242 USA Univ Iowa IIHR Hydrosci & Engn Iowa City IA 52242 USA

The main contribution of this interdisciplinary work is a robust computational framework to autonomously discover and quantify previously unknown associations between well-known (target) and potentially unknown (non-target) toxic industrial air pollutants. In this work, the variability of polychlorinated biphenyl (PCB) data is evaluated using a combination of statistical, signal processing, and graph-based informatics techniques to interpret the raw instrument signal from gas chromatography-mass spectrometry (GC/MS/MS) data sets. Specifically, minimum mean-squared techniques from the adaptive signal processing literature are extended to detect and separate coeluted (overlapped) peaks in the raw instrument signal. A graph-based visualization is provided which bridges two complementary approaches to quantitative pollution studies: (i) peak-cognizant target analysis (limits data analysis to few well-known compounds) and (ii) chemometric analysis (statistical large-scale data analysis) that is agnostic of specific compounds. Further, peak fitting techniques based on L2 error minimization are employed to autonomously calculate the amount of each PCB present with a normalized mean square error of -18.4851 dB. Graph-based visualization of associations between known and unknown compounds are developed through principal component analysis and both fuzzy c-means (FCM) and k-means clustering techniques are implemented and compared. The efficiency of these methods are compared using 150 air samples analyzed for individual PCBs with GC/MS/MS against traditional target-only techniques that perform analysis across only the known (target) PCBs. Parameter optimization techniques are employed to evaluate the relative contribution of PCB signals against ten potential source signals representing legacy signatures from historical manufacture of Aroclors and modern sources of PCBs produced as byproducts of pigment and polymer manufacturing. Aroclors 1232, 1254, 1016, and 1221 as well as

关键词： Instruments Compounds signal processing Principal component analysis Chemicals Load modeling signal processing algorithms Identifying sources interpreting GC MS MS PCBs signal processing

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VLSI SYSTEM COMPILER FOR DIGITAL signal-processing - MODULARIZATION AND SYNCHRONIZATION

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS 1991年第4期38卷 423-433页

作者： ITO, K KUNIEDA, H Department of Electrical and Electronic Engineering Tokyo Institute of Technology Meguro Tokyo Japan

An overview of a VLSI system compiler that generates a highly parallel and fast processor array on a VLSI chip for general digital signal processing algorithms is described here. In line with this overview, this paper describes the modularization and the synchronization of general digital signal processing algorithms that convert them into suitable forms for the implementation by a processor array on a VLSI chip. First, signal processing algorithms are modularized into the minimum number of inner-product modules by the proposed modularization procedure. Modularizing digital signal processing algorithms with the low coefficient sensitivity parameters is also proposed. Then these modules are assigned to inner-product processors. After processors are placed and communication paths between them are routed on a VLSI chip, the synchronization procedure derives a schedule for this VLSI system. When data transfer conflict occurs on interprocessor communications links and operation execution conflict occurs on processors, how they are resolved is discussed in this paper.

关键词： Very large scale integration Digital signal processing signal processing algorithms Processor scheduling Digital signal processing chips Parallel processing Systolic arrays Indium tin oxide signal generators signal resolution

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The development of a new signal processing program at the Queensland University of Technology

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IEEE TRANSACTIONS ON EDUCATION 1996年第2期39卷 186-191页

作者： Boashash, B Sridharan, S Chandran, V Signal Processing Research Center School of Electronic Systems Engineering Queensland University of Technology Brisbane Australia

The School of Electrical and Electronic Systems Engineering at Queensland University of Technology, Brisbane, Australia (QUT), offers three bachelor degree courses in electrical and computer engineering. In all its courses there is a strong emphasis on signal processing. A newly established signal processing Research Center (SPRC) has played an important role in the development of the signal processing units in these courses. This paper describes the unique design of the undergraduate program in signal professing at QUT, the laboratories developed to support it, and the criteria that influenced the design.

关键词： Biomedical signal processing signal processing algorithms signal processing Australia Digital signal processing signal design Biomedical engineering Geophysical signal processing Radar signal processing Systems engineering and theory

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Well-Log and Seismic Data Integration for Reservoir Characterization A signal processing and machine-learning perspective

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IEEE signal processing MAGAZINE 2018年第2期35卷 72-81页

作者： Chaki, Soumi Routray, Aurobinda Mohanty, William K. Indian Inst Technol Kharagpur Elect Engn Kharagpur W Bengal India Indian Inst Technol Kharagpur Dept Elect Engn Kharagpur W Bengal India Indian Inst Technol Kharagpur Dept Geol & Geophys Kharagpur W Bengal India

Reservoir characterization (RC) is a process of finding petrophysical properties of the subsurface mainly from the seismic and well-log data. The nonlinear and heterogeneous nature of the subsurface is the major bottleneck in estimating the reservoir properties. In the past two decades, the RC has eventually turned out to be an interdisciplinary field of research involving computational science, signal processing, geostatistics, and geophysics. This article provides the interdisciplinary perspective in RC focusing on the applications of signal processing and machine learning (ML). We provide an account of various state-of-the-art algorithms while categorizing them into three stages in an RC framework: preprocessing, prediction, and postprocessing. RC has been known to be a highly data-driven problem. Huge volumes of seismic and well-log data are cleverly integrated by experts to decipher the subsurface properties. Some of the anomalies may lead to the existence of a potential reservoir. The signal processing tools are primarily required for information matching, preprocessing for noise and artifacts, and postprocessing for removing irregularities in the prediction, whereas the ML tools are required to map the seismic data to well logs. This article provides a comprehensive study on the recent advances in RC involving seismic volumes and well logs.

关键词： Prediction algorithms signal processing algorithms Feature extraction Artificial neural networks signal resolution Reservoirs

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Hallway Gait Monitoring Using Novel Radar signal processing and Unsupervised Learning

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IEEE SENSORS JOURNAL 2022年第15期22卷 15133-15145页

作者： Abedi, Hajar Boger, Jennifer Morita, Plinio P. Wong, Alexander Shaker, George Univ Waterloo Syst Design Engn Dept Waterloo ON N2L 3G1 Canada Univ Waterloo Sch Publ Hlth Sci Waterloo ON N2L 3G1 Canada Univ Waterloo Elect Engn Dept Waterloo ON N2L 3G1 Canada

We propose a novel corridor or hallway gait monitoring system based on radar signal processing, unsupervised learning, and a subject detection, association and tracking method. This paper proposes an algorithm that could be paired with any type of MIMO FMCW radar to capture human gait in a highly cluttered environment without needing radar antenna alteration. We validate algorithm functionality by capturing spatiotemporal gait values (e.g., speed, step points, step time, step length, and step count) of people walking in a long hallway. We show that our proposed algorithm yields an average absolute error for speed estimation between 0.0040 m/s to 0.0435 m/s. These preliminary results demonstrate the promising potential of our algorithm to accurately monitor gait in hallways, which increases opportunities for its applications in institutional and home environments.

关键词： Radar Clutter signal processing algorithms Legged locomotion Sensors Radar antennas Monitoring Contactless monitoring doppler frequency-modulated continuous-wave multipath multiple-input and multiple-output radar gait analysis

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