By Hava T. Siegelmann
The theoretical foundations of Neural Networks and Analog Computation conceptualize neural networks as a specific form of machine inclusive of a number of assemblies of easy processors interconnected in an complicated constitution. interpreting those networks less than a variety of source constraints finds a continuum of computational units, numerous of which coincide with famous classical types. On a mathematical point, the therapy of neural computations enriches the speculation of computation but in addition explicated the computational complexity linked to organic networks, adaptive engineering instruments, and comparable types from the fields of regulate thought and nonlinear dynamics. the fabric during this publication may be of curiosity to researchers in numerous engineering and technologies disciplines. additionally, the paintings could provide the bottom of a graduate-level seminar in neural networks for machine technology students.
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Extra resources for Neural Networks and Analog Computation: Beyond the Turing Limit (Progress in Theoretical Computer Science)
Neural Networks and Analog Computation: Beyond the Turing Limit (Progress in Theoretical Computer Science) by Hava T. Siegelmann