About: Compression (functional analysis) is a research topic. Over the lifetime, 2934 publications have been published within this topic receiving 25946 citations.
TL;DR: An adaptive fast multipole method for the Laplace equation in three dimensions that uses both new compression techniques and diagonal forms for translation operators to achieve high accuracy at a reasonable cost.
TL;DR: The theoretical bases behind the direct ECG data compression schemes are presented and classified into three categories: tolerance-comparison compression, DPCM, and entropy coding methods and a framework for evaluation and comparison of ECG compression schemes is presented.
Abstract: Electrocardiogram (ECG) compression techniques are compared, and a unified view of these techniques is established. ECG data compression schemes are presented in two major groups: direct data compression and transformation methods. The direct data compression techniques are ECG differential pulse code modulation (DPCM) and entropy coding, AZTEC, Turning-point, CORTES, Fan and SAPA algorithms, peak-picking, and cycle-to-cycle compression methods. The transformation methods include Fourier, Walsh, and Karhunen-Loeve transforms. The theoretical bases behind the direct ECG data compression schemes are presented and classified into three categories: tolerance-comparison compression, DPCM, and entropy coding methods. A framework for evaluation and comparison of ECG compression schemes is presented. >
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TL;DR: This article summarizes and categories hardware-based test vector compression techniques for scan architectures, which fall broadly into three categories: code-based schemes use data compression codes to encode test cubes; linear-decompression- based schemes decompress the data using only linear operations; and broadcast-scan-based scheme rely on broadcasting the same values to multiple scan chains.
Abstract: Test data compression consists of test vector compression on the input side and response, compaction on the output side This vector compression has been an active area of research This article summarizes and categories these techniques The focus is on hardware-based test vector compression techniques for scan architectures Test vector compression schemes fall broadly into three categories: code-based schemes use data compression codes to encode test cubes; linear-decompression-based schemes decompress the data using only linear operations (that is LFSRs and XOR networks) and broadcast-scan-based schemes rely on broadcasting the same values to multiple scan chains
TL;DR: This property enables such compression schemes to be used in certain situations where the singular value decomposition (SVD) cannot be used efficiently.
Abstract: A procedure is reported for the compression of rank-deficient matrices A matrix A of rank k is represented in the form $A = U \circ B \circ V$, where B is a $k\times k$ submatrix of A, and U, V are well-conditioned matrices that each contain a $k\times k$ identity submatrix This property enables such compression schemes to be used in certain situations where the singular value decomposition (SVD) cannot be used efficiently Numerical examples are presented