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System design, signal-processing procedures, and preliminary results for the Canadian (London, Ontario) VHF atmospheric radar

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RADIO SCIENCE 1997年第2期32卷 687-706页

作者： Hocking, WK Department of Physics University of Western Ontario London Ontario Canada

Hardware, software, and design features of a new VKF atmospheric radar situated in Canada are described, with particular emphasis being placed on the flexibility which has been implemented at quite low cost. Called CLOVAR (Canadian (London, Ontario) VHF atmospheric radar), the instrument has now been operational since November 1993. It is located at 43 degrees 04.44'N, 81 degrees 20.20'W, operates at a frequency of 40.68 MHz, and is owned and operated by the nearby University of Western Ontario in London, Ontario, Canada. There are some unique features about this system, including its low-cost design, flexible beam-steering, and on-line software analysis procedures. In this paper we elaborate on these new developments and especially demonstrate the new signal processing algorithms currently in use. These new algorithms include procedures for rejection of signals due to aircraft, removal of instrumental drift, and full on-line spectral fitting of Gaussian functions. Typical data from the system are presented, including experimental data acquired with multibeam experiments, monthly mean vertical velocities, and some interesting results obtained during a solar eclipse. The radar can also function as an efficient meteor radar for determination of high-level winds, and this capability will also be briefly described. A special program of comparisons with colocated radiosonde flights is also discussed.

关键词： signal processing algorithms Radar antennas Switches Algorithm design and analysis Spaceborne radar

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TOOLS FOR REAL-TIME signal-processing RESEARCH

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IEEE COMMUNICATIONS MAGAZINE 1993年第11期31卷 64-74页

作者： SNYDER, JH QUACKENBUSH, SR MELCHNER, MJ KAPILOW, DA AT&T BELL LABS DEPT SPEECH CODING RESMURRAY HILLNJ 07974 AT&T BELL LABS INTERACT SYST RES DEPTMURRAY HILLNJ 07974

The use of digital signal processing (DSP) devices for real-time communication applications is discussed. The authors comment on distinguishing aspects of DSP architecture, describing not so much individual processors as those features common to DSPs and distinct from modern general-purpose processors. They describe three DSP32xx-based machines that support DSP algorithm implementation: SURF-board, HoBo, and DSP3. They also described rtpi, a source-code debugger for workstations and for the AT&T DSP32C signal-processor integrated circuit, and dspx, a collection of subroutines and host programs that provides an execution environment for DSPs akin to the UNIX environment. These tools facilitate the transfer of algorithms from mainframes or workstations to DSP hardware. Included are case studies of two real-time implementations: the low-delay CELP (LD-CELP) speech coder and the decoder side of the perceptual audio coder (PAC), an algorithm that compresses CD-quality audio into a 128-kb/s stream without perceptible distortion.< >

关键词： signal processing algorithms Digital signal processing Hardware signal processing Digital signal processing chips Workstations Testing Erbium Trademarks Assembly

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RECURSIVE PRUNING OF THE 2-D DFT WITH 3-D signal-processing APPLICATIONS

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IEEE TRANSACTIONS ON signal processing 1993年第3期41卷 1340-1356页

作者： KNUDSEN, KS BRUTON, LT UNIV CALGARY DEPT ELECT & COMP ENGNCALGARY T2N 1N4ALBERTACANADA

A recursively pruned radix-(2 x 2) two-dimensional (2-D) fast Fourier transform (FFT) algorithm is proposed which reduces the number of operations involved in the calculation of the 2-D discrete Fourier transform (DFT). It is able to compute input and output data points having multiple and possibly irregularly shaped (that is, nonsquare) regions of support. The computational performance of the recursively pruned radix-(2 x 2) 2-D FFT algorithm is compared with that of pruning algorithms based on the one-dimensional (1-D) FFT. The proposed recursively pruned 2-D FFT algorithm is shown to yield significant computational savings when employed in the recently proposed combined 2-D DFT/1-D linear difference equation filter method to enhance three-dimensional spatially planar image sequences, and when employed in the MixeD moving object detection and trajectory estimation algorithm.

关键词： signal processing signal processing algorithms Discrete Fourier transforms Two dimensional displays Fast Fourier transforms Image sequences Least squares approximation Flow graphs Difference equations

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Multiobjective signal processing Optimization [The way to balance conflicting metrics in 5G systems]

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IEEE signal processing MAGAZINE 2014年第6期31卷 14-23页

作者： Bjoernson, Emil Jorswieck, Eduard Debbah, Merouane Ottersten, Bjoern KTH Royal Inst Technol Stockholm Sweden Heinrich Hertz Inst Berlin Fraunhofer Inst Telecommun Berlin Germany Tech Univ Berlin Berlin Germany Tech Univ Dresden Dresden Germany Vienna Res Ctr Telecommun Vienna Austria Inst Eurecom Mobile Commun Dept Sophia Antipolis France

The evolution of cellular networks is driven by the dream of ubiquitous wireless connectivity: Any data service is instantly accessible everywhere. With each generation of cellular networks, we have moved closer to this wireless dream; first by delivering wireless access to voice communications, then by providing wireless data services, and recently by delivering a WiFi-like experience with wide-area coverage and user mobility management. The support for high data rates has been the main objective in recent years, as seen from the academic focus on sum-rate optimization and the efforts from standardization bodies to meet the peak rate requirements specified in IMT-Advanced. In contrast, a variety of metrics/objectives are put forward in the technological preparations for 5G networks: higher peak rates, improved coverage with uniform user experience, higher reliability and lower latency, better energy efficiency, lower-cost user devices and services, better scalability with number of devices, etc. These multiple objectives are coupled, often in a conflicting manner such that improvements in one objective lead to degradation in the other objectives. Hence, the design of future networks calls for new optimization tools that properly handle the existence and tradeoffs between multiple objectives. In this article, we provide a review of multi-objective optimization (MOO), which is a mathematical framework to solve design problems with multiple conflicting objectives. (...) We provide a survey of the basic definitions, properties, and algorithmic tools in MOO. This reveals how signal processing algorithms are used to visualize the inherent conflicts between 5G performance objectives, thereby allowing the network designer to understand the possible operating points and how to balance the objectives in an efficient and satisfactory way. For clarity, we provide a case study on massive MIMO.

关键词： 5G mobile communication Next generation networking Cellular networks Wireless communication signal processing algorithms Ubiquitous computing Mobile radio mobility management Wireless cellular networks

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Achieving Robustness in Blind Modulo Analog-to-Digital Conversion

Achieving Robustness in Blind Modulo Analog-to-Digital Conve...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Amir Weiss Faculty of Engineering BarIlan University

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

The need to digitize signals with intricate spectral characteristics often challenges traditional analog-to-digital converters (ADCs). The recently proposed modulo-ADC architecture offers a promising alternative by leveraging inherent features of the input signals. This approach can dramatically reduce the number of bits required for the conversion while maintaining the desired fidelity. However, the core algorithm of this architecture, which utilizes a prediction filter, functions properly only when the respective prediction error is bounded. In practice, this assumption may not always hold, leading to considerable instability and performance degradation. To address this limitation, we propose an enhanced modulo-unfolding solution without this assumption. We develop a reliable detector to successfully unfold the signals, yielding a robust solution. Consequently, the reinforced system maintains proper operation in scenarios where the original approach fails, while also reducing the quantization noise. We present simulation results that demonstrate the superior performance of our approach in a representative setting.

关键词： Quantization (signal) Simulation Noise Stability criteria signal processing algorithms Filtering algorithms Robustness Speech processing Analog-digital conversion Sensor arrays

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Robust Exponential Hyperbolic Tangent Geman-McClure Based Identification of Nonlinear Systems

Robust Exponential Hyperbolic Tangent Geman-McClure Based Id...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Neetu Chikyal Vasundhara Chayan Bhar Asutosh Kar Mads Græsbøll Christensen Vasavi College of Engineering Hyderabad Telangana Department of Electronics and Communication Engineering National Institute of Technology Warangal India Dr B R Ambedkar National Institute of Technology Jalandhar Punjab Department of Electronic Systems Aalborg University Denmark

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

This manuscript presents a new technique to improve the performance of adaptive filters in handling the non-Gaussian or impulsive noise environment. The conduct of the adaptive filter decays in the presence of impulsive noise or outliers. To improve the efficiency of the filtering technique, this work presents a robust exponential hyperbolic tangent Geman McClure function for nonlinear system identification. The algorithm utilizes the saturation properties of the hyperbolic tangent function to improve the performance under impulsive noise. The simulation results clearly illustrate the potency of the suggested technique.

关键词： Filtering Simulation Noise signal processing algorithms Adaptive filters Acoustics Nonlinear systems Speech processing

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Real-Time Wild Animal Detection using YOLOv10 Algorithm

Real-Time Wild Animal Detection using YOLOv10 Algorithm

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International Conference on Wireless Communications, signal processing and Networking (WiSPNET)

作者： Nishanth I Rakeshkumar R Thenmozhi V Department of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Chennai India

ISBN: (数字)9798331524227

ISBN: (纸本)9798331524234

This project utilizes the YOLOv10 algorithm on the NVIDIA Jetson Nano board to create a real-time wild animal detection system. By continuously analyzing video feeds from wildlife monitoring setups, the system accurately and efficiently detects animals across diverse environmental conditions. Leveraging the Jetson Nano’s edge computing capabilities alongside YOLOv10’s advanced object detection, the research presents a cost-effective, low-power solution for automated wildlife monitoring. With its ability to continuously track and identify animals in remote areas, this approach enhances conservation efforts and provides valuable data for biodiversity studies and the protection of endangered species.

关键词： YOLO Wireless communication Animals Biological system modeling Surveillance Wildlife signal processing algorithms Streaming media Real-time systems Environmental management

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Sequential Decoding of Multiple Traces Over the Syndrome Trellis for Synchronization Errors

Sequential Decoding of Multiple Traces Over the Syndrome Tre...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Anisha Banerjee Lorenz Welter Alexandre Graell I Amat Antonia Wachter-Zeh Eirik Rosnes Institute for Communications Engineering Technical University of Munich (TUM) Munich Germany Department of Electrical Engineering Chalmers University of Technology Gothenburg Sweden Simula UiB Bergen Norway

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Standard decoding approaches for convolutional codes, such as the Viterbi and BCJR algorithms, entail significant complexity when correcting synchronization errors. The situation worsens when multiple received sequences should be jointly decoded, as in DNA storage. Previous work has attempted to address this via separate-BCJR decoding, i.e., combining the results of decoding each received sequence separately. Another attempt to reduce complexity adapted sequential decoders for use over channels with insertion and deletion errors. However, these decoding alternatives remain prohibitively expensive for high-rate convolutional codes. To address this, we adapt sequential decoders to decode multiple received sequences jointly over the syndrome trellis. For the short blocklength regime, this decoding strategy can outperform separate-BCJR decoding under certain channel conditions, in addition to reducing decoding complexity. To mitigate the occurrence of a decoding timeout, formally called erasure, we also extend this approach to work bidirectionally, i.e., deploying two independent stack decoders that simultaneously operate in the forward and backward directions.

关键词： Convolutional codes Viterbi algorithm signal processing algorithms DNA signal processing Decoding Complexity theory Synchronization Speech processing Standards

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FAULT-TOLERANT MATRIX ARITHMETIC AND signal-processing ON HIGHLY CONCURRENT COMPUTING STRUCTURES

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PROCEEDINGS OF THE IEEE 1986年第5期74卷 732-741页

作者： JOU, JY ABRAHAM, JA UNIV ILLINOIS DEPT ELECT & COMP ENGNURBANAIL 61801 UNIV ILLINOIS DEPT COMP SCIURBANAIL 61801 UNIV ILLINOIS COORDINATED SCI LABURBANAIL 61801

Hardware for executing matrix arithmetic and signal processing algorithms at high speeds is in great demand in many real-time and scientific applications. With the advent of VLSI technology, large numbers of processing elements which cooperate with each other at high speed have become economically feasible. Since any functional error in a high-performance system may seriously jeopardize the operation of the system and its data integrity, some level of fault tolerance must be incorporated in order to ensure that the results of long computations are valid. Since the major computational requirements for many important real-time signal processing tasks can be reduced to a common set of basic matrix operations, the development of a unified fault-tolerant scheme for matrix operations can solve the problems of both reliable signal processing and reliable matrix operations. Earlier work proposed a low-cost checksum scheme for fault-tolerant matrix operations on multiple processor systems. However, this scheme can only correct errors in matrix multiplication; it can detect, but not correct, errors in matrix-vector multiplication, LU decomposition, matrix inversion, etc. In order to solve these problems with the checksum scheme, a very general matrix encoding scheme is proposed in this paper to achieve fault-tolerant matrix arithmetic and signal processing with linear arrays, which are believed to hold the most promise in VLSI computing structures for their flexibility, low cost, and applicability to most of the interesting algorithms. This proposed technique is, therefore, a very cost-effective encoding technique to achieve fault-tolerant matrix arithmetic and signal processing on highly concurrent VLSI computing structures.

关键词： Fault tolerance Arithmetic signal processing Concurrent computing Matrix decomposition signal processing algorithms Very large scale integration Fault tolerant systems Error correction Encoding

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Graphon Filters: Graph signal processing in the Limit

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IEEE TRANSACTIONS ON signal processing 2021年 69卷 1740-1754页

作者： Morency, Matthew W. Leus, Geert Delft Univ Technol EWI NL-2628 CD Delft Netherlands

Graph signal processing is an emerging field which aims to model processes that exist on the nodes of a network and are explained through diffusion over this structure. Graph signal processing works have heretofore assumed knowledge of the graph shift operator. Our approach is to investigate the question of graph filtering on a graph about which we only know a model. To do this we leverage the theory of graphons proposed by L. Lovasz and B. Szegedy. We make three key contributions to the emerging field of graph signal processing. We show first that filters defined over the scaled adjacency matrix of a random graph drawn from a graphon converge to filters defined over the Fredholm integral operator with the graphon as its kernel. Second, leveraging classical findings from the theory of the numerical solution of Fredholm integral equations, we define the Fourier-Galerkin shift operator. Lastly, using the Fourier-Galerkin shift operator, we derive a graph filter design algorithm which only depends on the graphon, and thus depends only on the probabilistic structure of the graph instead of the particular graph itself. The derived graphon filtering algorithm is verified through simulations on a variety of random graph models.

关键词： signal processing Kernel signal processing algorithms Eigenvalues and eigenfunctions Fourier transforms Convergence Laplace equations Graph signal processing graph filter design graphons random graphs

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