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Extra resources for 58.Speech and Audio Processing
Briggs, Computer Architecture and Parallel Processing, New York: McGraw-Hill, 1984. R. E. Kessler and J. L. Schwarzmeier, Cray T3D: A new dimension for Cray Research, IEEE Int. Comput. Conf. CompCon, 1993, pp. 176–182. N. Koike, NEC Cenju-3: A microprocessor-based parallel computer multistage network, 8th Int. Parallel Process. , 1994, pp. 393–401. C. B. , The SP2 high-performance switch, IBM Syst. , 34 (2): 185–202, 1995. L. W. Tucker and G. G. , 21 (8): 26–38, 1988. Papers That Cover Network Fault Tolerance G.
XtϪ1 and xtϩ1, xtϩ2, . , xtϩL from a window as input to the MLP to relax the independence assumption equation [Eq. (8)]. Common values are L Յ 4, but there are also systems that use up to L ϭ 15. The size of ;; ;; ;;; NEURAL NETS FOR SPEECH PROCESSING 327 Output neuron group Hidden (state) neuron groups z –1 Inputs Group of weights with information flow z –1 Delay line t–1 (a) (b) the hidden layer is in general between 64 and 4096 neurons, depending on the amount of available training data, which results in about 10,000 to 2 million weights.
This protocol divides the search into two phases, similarly to the k-family routing protocol. Each phase is determined by the current distance between the message and its destination. If the distance is larger than a parameter d, then the protocol will use an exhaustive profitable search. If the message is closer to its destination than d, then the protocol switches to an exhaustive misrouting search. Because the second phase can route the message further away from its destination again, the search may switch between the two phases multiple times.