This paper proposes a new correlation matrix network model of associative memory in brain. Each memorized pattern which consists of binary (+1 or -1) elements is preprocessed by a quantized Hadamard transform to increase selectivity. The association ability of a correlation matrix network model depe
β¦ LIBER β¦
Nonlinear quantization on Hebbian-type associative memories
β Scribed by Chishyan Liaw, Ching-Tsorng Tsai, Chao-Hui Ko
- Book ID
- 113061000
- Publisher
- Springer US
- Year
- 2011
- Tongue
- English
- Weight
- 493 KB
- Volume
- 36
- Category
- Article
- ISSN
- 0924-669X
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