Results 21 to 30 of about 3,267,859 (298)
Flash-Based Computing-in-Memory Architecture to Implement High-Precision Sparse Coding
Micromachines, 2023 To address the concerns with power consumption and processing efficiency in big-size data processing, sparse coding in computing-in-memory (CIM) architectures is gaining much more attention.
Yueran Qi +9 more
doaj +1 more source
Gaussian and sparse processes are limits of generalized Poisson processes [PDF]
Applied and Computational Harmonic Analysis, 2020 The theory of sparse stochastic processes offers a broad class of statistical models to study signals. In this framework, signals are represented as realizations of random processes that are solution of linear stochastic differential equations driven by white Lévy noises.
Fageot, Julien +2 more
openaire +4 more sources
Sparse Gaussian Processes on Discrete Domains [PDF]
IEEE Access, 2021 IEEE Access ...
Vincent Fortuin +3 more
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Large-Scale Visualization of Sparse Matrices [PDF]
, 2014 An efficient algorithm for parallel acquisition of visualization data for large sparse matrices is presented and evaluated both analytically and empirically.
Tvrdik, P. +3 more
core +1 more source
RSNN: A Software/Hardware Co-Optimized Framework for Sparse Convolutional Neural Networks on FPGAs
IEEE Access, 2021 Convolutional Neural Networks (CNNs) have been shown to be very useful in image recognition and other Artificial Intelligence (AI) applications, however, at the expense of intensive computation requirement.
Weijie You, Chang Wu
doaj +1 more source
Asynchronous processing of sparse signals
IET Signal Processing, 2014 Unlike synchronous processing, asynchronous processing is more efficient in biomedical and sensing networks applications as it is free from aliasing constraints and quantization error in the amplitude, it allows continuous–time processing and more importantly data is only acquired in significant parts of the signal. We consider signal decomposers based
Azime Can-Cimino +2 more
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Audio Source Separation Using Sparse Representations [PDF]
, 2010 This is the author's final version of the article, first published as A. Nesbit, M. G. Jafari, E. Vincent and M. D. Plumbley. Audio Source Separation Using Sparse Representations. In W.
Nesbit, Andrew +7 more
core +1 more source
Sparse Multiscale Patches for Image Processing [PDF]
, 2009 This paper presents a framework to define an objective measure of the similarity (or dissimilarity) between two images for image processing. The problem is twofold: 1) define a set of features that capture the information contained in the image relevant for the given task and 2) define a similarity measure in this feature space.
Piro, Paolo +3 more
openaire +3 more sources
Improved sparse representation using adaptive spatial support for effective target detection in hyperspectral imagery [PDF]
, 2013 With increasing applications of hyperspectral imagery (HSI) in agriculture, mineralogy, military, and other fields, one of the fundamental tasks is accurate detection of the target of interest.
Li, Xiaohui +3 more
core +4 more sources
Regularized Sparse Gaussian Processes
CoRR, 2019 Gaussian processes are a flexible Bayesian nonparametric modelling approach that has been widely applied but poses computational challenges. To address the poor scaling of exact inference methods, approximation methods based on sparse Gaussian processes (SGP) are attractive.
Rui Meng +3 more
openaire +2 more sources