Soft commutation in capacitive idling converters

The capacitive idling converters derived from the Cuk, SEPIC, Zeta, and flyback topologies allow soft commutation of power switches without the need for additional circuitry, making it possible to increase the switching frequency while maintaining high efficiency     

Quantization effects in digitally behaving circuit implementationsof Kohonen networks

Implementing a neural network on a digital or mixed analog and digital chip yields the quantization of the synaptic weights dynamics. This paper addresses this topic in the case of Kohonen's self-organizing maps. We first study qualitatively how the quantization affects the convergence and the properties, and deduce from this analysis the way to choose the parameters of the network (adaptation gain and neighborhood). We show that a spatially decreasing neighborhood function is far more preferable than the usually rectangular neighborhood function, because of the weight quantization. Based on these results, an analog nonlinear network, integrated in a standard CMOS technology, and implementing this spatially decreasing neighborhood function is then presented. It can be used in a mixed analog and digital circuit implementation.     

Pipelining and bypassing in a VLIW processor

This short note describes issues involved in the bypassing mechanism for a very long instruction word (VLIW) processor and its relation to the pipeline structure of the processor. The authors first describe the pipeline structure of their processor and analyze its performance and compare it to typical RISC-style pipeline structures given the context of a processor with multiple functional units. Next they study the performance effects of various bypassing schemes in terms of their effectiveness in resolving pipeline data hazards and their effect on the processor cycle time     

Genetic evolution of the topology and weight distribution of neuralnetworks

This paper proposes a system based on a parallel genetic algorithm with enhanced encoding and operational abilities. The system, used to evolve feedforward artificial neural networks, has been applied to two widely different problem areas: Boolean function learning and robot control. It is shown that the good results obtained in both cases are due to two factors: first, the enhanced exploration abilities provided by the search-space reducing evolution of both coding granularity and network topology, and, second, the enhanced exploitational abilities due to a recently proposed cooperative local optimizing genetic operator.     

Large-deviation inequalities for parameter estimators in stochastic systems

Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 95–112, March–April, 1994.     

Changes of the combustion regimes of nongasifying and low-gas systems over the parameter range

The process of combustion of homogeneous and heterogeneous nongasifying and slightly gasifying systems over the range of a number of parameters characterizing the reactive composition and the conditions for the arrangement of the combustion process is studied by using thermocouple and optical methods. The regions of the implementation of different combustion regimes, namely, steady, pulsating, multiple-point, and spin, are determined experimentally.Institute of Structural Macrokinetics, Russian Academy of Sciences, Chernogolovka. Translated from Inzhenerno-Fizicheskii Zhurnal, Vol. 65, No. 4, pp. 407–411, October, 1993.     

Long range peak demand forecasting under conditions of high growth

An extended logistic model with a varying asymptotic upper bound for long-range peak demand forecasting is described. The model has been applied to a typical fast growing system, the Saudi Consolidated Electric Company. The forecasts are compared with actual demands and with those obtained from classical forecasting methods. The model gave relatively accurate peak demand forecasts compared with other classical methods. The model with a single load observation is capable of producing several peak demand forecasts corresponding to different levels of maximum temperature and various levels of social activity. The forecasts produced by the model were also stable irrespective of the length of the ex-post simulation period