Title :
Multi-pattern real-valued spectral associative memories
Author_Institution :
Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
Abstract :
A multi-pattern encoding and decoding scheme is presented that extends the family of spectral associative memories (SAMs) to include gray-level, or analog patterns. SAMs are frequency-domain formulations of associative memory that combine the extrinsic redundancy of neural networks with the in-phase, quadrature, and complex modulation schemes of communications. Considerable coding gain occurs at the level of modulation and these networks may be regarded as multi-channel, multi-carrier generalizations of amplitude modulation. Unlike multi-pattern bipolar SAMs, which are exclusively content-addressable, real-valued SAMs also have an addressable mode in which the recall of a particular memory may be forced. Band structures and anti-aliasing constraints are presented along with a probabilistic formulation in which virtual entanglement is a natural feature. Simulations are presented that demonstrate dual-memory recall for 6×6 gray-level patterns
Keywords :
content-addressable storage; decoding; eigenvalues and eigenfunctions; encoding; frequency-domain analysis; neural nets; probability; singular value decomposition; amplitude modulation; anti-aliasing constraints; decoding; eigenvalues; frequency-domain analysis; gray-level; multiple-pattern encoding; neural networks; probability; singular value decomposition; spectral associative memories; Active appearance model; Amplitude modulation; Associative memory; Convolution; Decoding; Eigenvalues and eigenfunctions; Frequency domain analysis; Modulation coding; Neural networks; Nonvolatile memory;
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7044-9
DOI :
10.1109/IJCNN.2001.939528