Method for data compression utilizing pattern-analysis and matching means such as neural networks

摘要

A new method for data compression utilizing a neural network or other statistical technique or pattern analysis is presented. This method represents the input data as a series of vectors (21) and uses any number of error functions to guide manipulation of a matrix (35) which stores similar vectors, as well as manipulating the vectors stored within. This matrix (35), which may be of any number of dimensions, any size in each of these dimensions, acts as a lookup table in the encoding and decoding processes of the compression method. Encoding works by comparing each sequential input vector (21) to the vector stored within the matrix (35) and writing the matrix address (45) which most closely represents the input vector (21). Decoding works by reading a series of matrix addresses (45) and sequentially outputting the corresponding vector stored within each matrix address (45). As such, both the storage matrix (35) and address series (45) are needed to represent and decode the compressed data; these parts may or may not be stored separately. This method can operate with or without the use of psychoacoustic or other perceptual models, with or without the use of Fourier or other transforms, and with or without the use of multiple input/output channels.