Neural networks Bidirectional associative memory

Schierle and Otto [63] used a two-layer perceptron with error back-propagation for quantitative analysis in ICP-AES. Also, Schierle et al. [64] used a simple neural network [the bidirectional associative memory (BAM)] for qualitative and semiquantitative analysis in ICP-AES. 

Some historically important artificial neural networks are Hopfield Networks, Per-ceptron Networks and Adaline Networks, while the most well-known are Backpropa-gation Artificial Neural Networks (BP-ANN), Kohonen Networks (K-ANN, or Self-Organizing Maps, SOM), Radial Basis Function Networks (RBFN), Probabilistic Neural Networks (PNN), Generalized Regression Neural Networks (GRNN), Learning Vector Quantization Networks (LVQ), and Adaptive Bidirectional Associative Memory (ABAM). 

The bidirectional associative memory (BAM) is used here to explain the operation of a neural network in more detail. 

B. Lenze, Neural Networks, 11, 1041 (1998). Complexity Preserving Increase of the Capacity of Bidirectional Associative Memories by Dilation and Translation. 

There is nothing like the neural network . Many types of neural networks have been proposed and used for various purposes, like Hopfield networks,the adaptive bidirectional associative memory,the Kohonen network, and radial basis funetion For the con-... 

ANN = artificial neural network AR = approximate reasoning BAM = bidirectional associative memory FAM = fuzzy associative memory FL = fuzzy logic LP = linear programming OLS = ordinary least squares PCCF = partial cross correlation function SSC = spectrum-structure correlation sup = supremum = fuzzy addition = fuzzy subtraction O = fuzzy multiplication Q = fuzzy division Q = relation. 

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