Titlebook: Neural Models and Algorithms for Digital Testing; Srimat T. Chakradhar,Vishwani D. Agrawal,Michael L Book 1991 Springer Science+Business M

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Parallel Processing Preliminaries,. One method uses an array of cooperating processors, suitably synchronized by a clocking mechanism, such that each develops a part of the solution that it shares with other neighbors. The other method uses . and is a radically different way of parallel processing. These networks are interconnection

Peristalsis

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Test Generation Reformulated,ulation captures three . and . conditions that any set of signal values must satisfy to be a test. First, the set of values must be consistent with each gate’s function in the circuit. Second, the signal in the fault-free and faulty circuits at the fault site must assume opposite values (e.g., 0 and

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Simulated Neural Networks,etworks [2, 5]. We describe algorithms for simulating the neural network on a serial computer and discuss possible implementations of these algorithms on parallel computers. Chapter 8 discusses test generation on a commercial hardware accelerator for neural network simulatioa

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Neural Computers,roblem for digital circuits. In later chapters, we will research several applications of the discrete models. However, the real neurons are analog elements and we must examine how well the present solution will work if actual neural network hardware was available. In this chapter, we present a solut

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