A unified diode model for circuit simulation

A new commercially available diode model is described. This unified model is capable of simulating the widest range of diode technologies of any presently available. The emphasis of this paper is on describing the model's extensive features and flexibility in the different domains of operation and is of particular interest in power applications     

Conditions for reliable dewatering systems based on voidless drainage in slightly permeable soils

Conclusions 1. Use of dewatering systems based on voidless drainage is most effective when dewatering slightly permeable soils in regions with a deep seasonal frost. 2. Two-story drainage with the upper and lower stories spaced 30 m apart accelerates the discharge of gravitational water from the arable layer. Results of observations on two-story drainage in experimental-production sections indicated that it discharges 2 – 3.8 times more water than systematic tubular drainage with an interdrain spacing of 10 m and a 0.2-m thick three-dimensional filter of a sandy-gravelly mixture. 3. It is recommended to use crushed stone and porous-clay gravel with a fineness of 10 – 20 mm as a filler. In that case, protection of the drain filler is, as a rule, required only from the intrusion of soil from above during construction in cohesive soils with a plasticity indexW _p≥7. 4. seepage rate in a voidless drain should be lower than the scouring velocity for the soil in which the voidless drainage is placed. In the opposite case, it is necessary to lower the grade of the drains or select a filler gradation such that the seepage rate in the drain be lower than the scouring velocity. Translated from Gidrotekhnicheskoe Stroitel’stvo, No. 8, pp. 41–43, August, 1998.     

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.     

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.     

Components of random generation by normal subjects and patients with dysexecutive syndrome

The study presents a hypothesis on how randomness could be simulated by human subjects. Three sources of deviation from randomness are predicted: (1) the preferred application of overlearned production schemata for producing sequences of digits, (2) a wrong concept of randomness, and (3) the impossibility to monitor for redundancies of higher- than those of first-order. Deviations of random generation of digits produced by healthy subjects, patients with chronic frontal lobe damage, and patients with Parkinson's disease from random sequences produced by a computer program can be explained by the differential influence of these factors. Whereas incorrect concepts of randomness and limits on monitoring capacity distinguished all sequences produced by humans from actual random sequences, persistence on a single production strategy distinguished brain-damaged patients from controls. Random generation of digits appears to be a theoretically transparent and clinically useful test of executive function.