Method and apparatus for encoding and decoding data utilizing data compression and neural networks
AssigneeU.S. Philips Corporation
InventorsJacques A. Sirat, Jean-Renaud Viala, Christian Remus
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AssigneeU.S. Philips Corporation
InventorsJacques A. Sirat, Jean-Renaud Viala, Christian Remus
Estimating the term…
A method structure for the compression of data utilizes an encoder which effects a transform with the aid of a coding neural network, and a decoder which includes a matched decoding neural network with effects almost the inverse transform of the encoder. The method puts in competition M coding neural networks (30.sub.1 to 30.sub.M) wherein M>1 positioned at the transmission end which effects a same type of transform and the encoded data of one of which are transmitted, after selection (32, 33) at a given instant, towards a matched decoding neural network which forms part of a set of several matched neural networks (60.sub.1 to 60.sub.Q) provided at the receiver end. Learning is effected on the basis of predetermined samples. The encoder may comprise, in addition to the coding neural network (30.sub.1 to 30.sub.M), a matched decoding neural network (35.sub.1 to 35.sub.M) so as to effect the selection (32, 33) of the best coding neural network in accordance with an error criterion.
A data compression method which is put into effect with the aid of an encoder for transforming input data with the aid of a coding neural network provided at a transmission end of a channel, said coding neural network having a number (N) of input neurons greater than or equal to the number (P) of output neurons, and a decoder which comprises a decoding neural network which is matched to the coding neural network positioned at a receiving end of said channel for effecting the inverse transform of the encoder with a number (P) of input neurons less than or equal to the number (N) of output neurons, the method comprising the following steps:
A coding circuit for the compression of data, comprising M coding neural networks wherein M>1 which learn and thereafter effect the same type of transform and which are put in competition, each network having a number of input neurons greater than or equal to the number of output neurons, a selection circuit comprising means for selecting on the basis of a selection criterion, that coding neural network that effects the best encoding and transmitting the index and the encoded data of this selected neural network.
A decoding circuit for the decompression of data comprising M decoding neural networks wherein M>1, which effect the same type of transform, each neural network having a number of input neurons less than the number of output neurons, there being assigned to each neural network an index which allows it to receive and decode only the encoded data associated with this index.
A data compression system comprising:
Dependencies are inferred from the claim text.