Dictionary Learning Algorithms for Sparse Representation - Kreutz-Delgado, Kenneth; Murray, Joseph F.; Rao, Bhaskar D.; Engan, Kjersti; Lee, Te-Won; Sejnowski, Terrence J. (Neural computation, 2003)
Keywords: Algorithms; Applied sciences; Artificial Intelligence; Biological and medical sciences; Computer science; control theory; systems; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; General aspects; General aspects. Models. Methods; Learning - physiology; Learning and adaptive systems; Mathematical foundations; Mathematics; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); Probability and statistics; Sciences and techniques of general use; Statistics; Stochastic Processes; Vertebrates: nervous system and sense organs; Stochastic model; Compression; Dictionaries; Description; Word; Noise; Complete; Elements; Generalization; Image; Mean square error; Learning; Probability density; Accuracy; Schur concavity; Gaussian noise; Noise source; Coding; Efficiency; Test; Bayesian model; A posteriori estimation; Sparse representation; Performance analysis; Component; Learning algorithm; Vector; Concept; Dictionary learning algorithm; Vector quantization; Use; Independent component analysis; Data; Representation; Neural network; Algorithm; Neurophysiology; Domains; Analysis method; Algorithm performance; Sparse set; Environment; Density function; Models; Maximum likelihood; Pixel; Signal to noise ratio