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multidimensional signal processing and detection for storage systems with data-dependent transition noise

IEEE TRANSACTIONS ON MAGNETICS 2006年第7期42卷 1905-1916页

作者： Pighi, Riccardo Raheli, Riccardo Amadei, Umberto Univ Parma Dipartimento Ingn Informaz I-43100 Parma Italy Selta SpA I-29010 Piacenza Italy

In the last decade, significant research on detection algorithms capable of mitigating the effects of colored Gaussian thermal noise and transition noise in storage systems, has been performed. In this paper, we present a new detection scheme based on a multidimensional detector front end and multidimensional linear prediction, applied to maximum a posteriori probability (MAP) sequence detection. This method improves the bit-error-rate (BER) performance with respect to previous approaches and makes the detector quite insensitive to transition noise. We show that the gain in terms of BER versus signal-to-noise ratio with our detector increases with the user density. The results obtained for a magnetic storage channel are extendable to optical storage systems as well.

关键词： longitudinal and perpendicular recording magnetic storage systems multidimensional linear prediction multidimensional signal processing optical storage systems transition noise

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multidimensional signal processing using quaternion complex Hadamard transform in sequency domain

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ELECTRONICS LETTERS 2018年第25期54卷 1435-+页

作者： Jabeen, D. Iqrar, T. Khan, M. Faisal Hamdard Univ Hamdard Inst Engn & Technol Dept Elect Engn Muhammad Bin Qasin Ave Karachi 74600 Pakistan

This Letter presents the quaternion conjugate symmetric-sequency ordered complex Hadamard transform (QCS-SCHT). The purpose of this research is to present the idea of the quaternion in sequency domain that is based on four complexified terms including real and imaginary values are discussed and developed with different types of quaternions planes for QCS-SCHT. QCS-SCHT is discussed for colour image processing.

关键词： Hadamard transforms image colour analysis sequency domain quaternions planes QCS-SCHT colour image processing multidimensional signal processing quaternion complex Hadamard transform quaternion conjugate symmetric sequency ordered complex Hadamard transform real value imaginary value

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multidimensional signal processing and Applications-New Approaches 3rd

Multidimensional Signal Processing and Applications-New Appr...

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International Workshop on New Approaches for multidimensional signal processing (NAMSP)

作者： Kountchev, Roumen Mironov, Rumen Draganov, Ivo Kountcheva, Roumiana Tech Univ Sofia 8 Kliment Ohridski Blvd Sofia 1756 Bulgaria TK Engn Sofia Bulgaria

ISBN: (纸本)9789811978449;9789811978425;9789811978418

This chapter is a short introduction in the contemporary approaches aimed at the multidimensional processing and analysis of various kinds of signals, investigated in related research works, which were presented at the Third International Workshop "New Approaches for multidimensional signal processing", (NAMSP), held at the Technical University of Sofia, Bulgaria in July 2022. Some of the works cover various topics, as: moving objects tracking in video sequences, automatic audio classification, representation of color video qpez 2-level tensor spectrum pyramid, etc., and also introduce multiple applications of the kind: analysis of electromyography signals, diagnostics of COVID based on ECG, etc. Short descriptions are given for the main themes covered by the book, which comprises the following three sections: multidimensional signal processing;applications of multidimensional signal processing, and applications of blockchain and network technologies.

关键词： multidimensional signal processing Tensor decomposition Deep learning Blockchain Medical decision support Audio classification Paraconsistent logic Deep faith network model Ant colony

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signal Assignment Model for the Memory Management of multidimensional signal processing Applications

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JOURNAL OF signal processing SYSTEMS FOR signal IMAGE AND VIDEO TECHNOLOGY 2011年第1期63卷 51-65页

作者： Balasa, Florin Luican, Ilie I. Zhu, Hongwei Nasui, Doru V. So Utah Univ Dept Comp Sci Cedar City UT 84720 USA Univ Illinois Dept Comp Sci Chicago IL USA ARM Inc Design Automat Grp Phys IP Dept Sunnyvale CA USA Amer Int Radio Inc Rolling Meadows IL USA

Many signal processing systems, particularly in the multimedia and telecom domains, are synthesized to execute data-dominated applications. Their behavior is described in a high-level programming language, where the code is typically organized in sequences of loop nests and the main data structures are multidimensional arrays. Since data transfer and storage have a significant impact on both the system performance and the major cost parameters-power consumption and chip area, the designer must spend a significant effort during the system development process on the exploration of the memory subsystem in order to achieve a cost-optimized design. This paper presents a memory allocation methodology for multidimensional signal processing applications, focusing on the problem of efficiently mapping the multidimensional signals from the algorithmic specification into the physical memory. In a first phase, two previous mapping models are implemented within a common theoretical framework, which is advantageous from both the point of view of computational efficiency and the amount of allocated data storage. Different from all the previous mapping models that aim to optimize the memory sharing between the elements of a same array (creating separate windows in the physical memory for distinct arrays), this proposed mapping model exploitin a second phase-the possibility of memory sharing between the elements of different arrays. As a consequence, this signal assignment approach yields significant savings in the amount of data storage resulted after mapping.

关键词： Memory management Memory allocation signal-to-memory assignment multidimensional signal processing Storage requirement

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MORPHOLOGICAL SYSTEMS FOR multidimensional signal-processing

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PROCEEDINGS OF THE IEEE 1990年第4期78卷 690-710页

作者： MARAGOS, P SCHAFER, RW GEORGIA INST TECHNOL SCH ELECT ENGN ATLANTA GA 30332 USA

The basic theory and applications of a set-theoretic approach to image analysis called mathematical morphology are reviewed. The goals are to show how the concepts of mathematical morphology geometrical structure in signals to illuminate the ways that morphological systems can enrich the theory and applications of multidimensional signal processing. The topics covered include: applications to nonlinear filtering (morphological and rank-order filters, multiscale smoothing, morphological sampling, and morphological correlation); applications to image analysis (feature extraction, shape representation and description, size distributions, and fractals); and representation theorems, which shows how a large class of nonlinear and linear signal operators can be realized as a combination of simple morphological operations

关键词： correlation theory feature extraction filtering and prediction theory fractals geometrical structure image analysis linear signal operators mathematical morphology morphological correlation morphological sampling multidimensional signal processing multiscale smoothing nonlinear filtering nonlinear signal operators picture processing rank-order filters representation theorems set theory set-theoretic approach shape representation size distributions

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Select Trends in Image, Video, and multidimensional signal processing

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IEEE signal processing MAGAZINE 2012年第1期29卷 174-176页

作者： Sharma, Gaurav Karam, Lina Wolfe, Patrick Univ Rochester Rochester NY 14627 USA Arizona State Univ Tempe AZ 85287 USA Harvard Univ Cambridge MA 02138 USA

The Image, Video, and multidimensional signal Pro cessing (IVMSP) title combines within it a broad scope of technical areas dealing with the representation, processing, analysis, classification, compression, and transmission of still images, video, and general multidimensional data. Within the IEEE signal processing Society, the IVMSP Technical Committee (IVMSP-TC) has the charter of promoting and guiding the advancement of these technical areas.

关键词： Image processing Video communication multidimensional signal processing

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A theorem in probability and its applications in multidimensional signal processing

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IEEE TRANSACTIONS ON signal processing 1996年第12期44卷 3167-3169页

作者： Kundu, D Bai, ZD Mitra, A NATL SUN YAT SEN UNIV DEPT MATH APPLKAOHSIUNG 80424TAIWAN

In this correspondence, we present a result in probability that does not exist in the literature of probability theory. We show one application of this theorem in multidimensional signal processing, which generalizes ... 详细信息

关键词： multidimensional signal processing Random variables Mathematics Government Strontium signal processing

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The past, present, and future of image and multidimensional signal processing

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IEEE signal processing MAGAZINE 1998年第2期15卷 21-58页

作者： Chellappa, R Girod, B Munson, DC Tekalp, M Vetterli, M su.edu

The field of image and multidimensional signal processing began as a field of strong theoretical framework based on mathematics, statistics, and physics. Later, with advances in computing, memory, and image-sensing technology, techniques developed for image enhancement, still and moving image compression, image understanding gave this field a solid base of practical applications. Furthermore, the exploding growth of the Internet and the ubiquity of images and video, the field of image and multidimensional signal processing is becoming more and more exciting. Topics covered in the article include: multidimensional signal-processing theory, image acquisition, image transforms, image modeling, image enhancement and restoration, image and video analysis, processing, coding, hardware and software implementation issues, and computed imaging.

关键词： image enhancement signal processing multidimensional signal processing Image Fields

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signal Assignment to Hierarchical Memory Organizations for Embedded multidimensional signal processing Systems

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IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS 2009年第9期17卷 1304-1317页

作者： Balasa, Florin Zhu, Hongwei Lucien, Ilie I. So Utah Univ Dept Comp Sci & Informat Syst Cedar City UT 84721 USA ARM Inc Phys IP Div San Jose CA 95134 USA Univ Illinois Dept Comp Sci Chicago IL 60607 USA

The storage requirements of the array-dominated and loop-organized algorithmic specifications running on embedded systems can be significant. Employing a data memory space much larger than needed has negative consequences on the energy consumption, latency, and chip area. Finding an optimized storage of the usually large arrays from these algorithmic specifications is an essential task of memory allocation. This paper proposes an efficient algorithm for mapping multidimensional arrays to the data memory. Similarly to [1], it computes bounding windows for live elements in the index space of arrays, but this algorithm is several times faster. More important, since this algorithm works not only for entire arrays, but also parts of arrays-like, for instance, array references or, more general, sets of array elements represented by lattices [2], this signal-to-memory mapping technique can be also applied in hierarchical memory architectures.

关键词： Lattice memory allocation multidimensional signal processing polytope signal-to-memory mapping

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Power and area minimization for multidimensional signal processing

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IEEE JOURNAL OF SOLID-STATE CIRCUITS 2007年第4期42卷 922-934页

作者： Markovic, Dejan Nikolic, Borivoje Brodersen, Robert W. Univ Calif Los Angeles Dept Elect Engn Los Angeles CA 90095 USA Univ Calif Berkeley Berkeley Wireless Res Ctr Berkeley CA 94704 USA

Sensitivity-based methodology is applied to optimization of performance, power and area across several levels of design abstraction for a complex wireless baseband signal processing algorithm. The design framework is based on a unified, block-based graphical description of the algorithm to avoid design re-entry in various phases of chip development. The use of architectural techniques for minimization of power and area for complex signal processing algorithms is demonstrated using this framework. As a proof of concept, an ASIC realization of the MIMO baseband signal processing for a multi-antenna WLAN is described. The chip implements a 4 x 4 adaptive singular value decomposition (SVD) algorithm with combined power and area minimization achieving a power efficiency of 2.1 GOPS/mW (12-bit add equivalent) in just 3.5 mm(2) in a standard 90 nm CMOS process. The computational throughput of 70 GOPS is implemented with 0.5 M cells at a 100 MHz clock and 385 mV supply, dissipating 34 mW of power. With optimal channel conditions the algorithm implemented can deliver up to 250 Mb/s over 16 sub-carriers.

关键词： circuit optimization CMOS digital integrated circuits design methodology field-programmable gate arrays matrix decomposition MIMO systems multidimensional signal processing parallel architectures pipelines sensitivity

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