Adaptive neural network algorithm for solving linear algebra problems

Discusses the construction of adaptive neural network algorithms for solving systems of linear equations and linear inequalities. The performance and efficiency are evaluated for parallel algorithms. An assessment is made of the gain in terms of throughput when neural network algorithms are used in terms of 'natural' implementation. The speed performance of an algorithm is proportional to the number of physically implemented linear threshold elements and may reach 2K.<
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