This paper presents a new approach to select number of hidden neurons in neural network in renewable energy systems. The random selection of number of hidden neurons might cause over fitting and under fitting problems in neural networks. The proper selection of neurons in hidden layer is important in the design of neural network model. To fix hidden neurons, 91 various criteria are examined bas...

In this contribution, we show that the incorporation of nonlinear dynamical measures into a multivariate discrimination provides a signal classification system that is robust to additive noise. The signal library was composed of nine groups of signals. Four groups were generated computationally from deterministic systems (van der Pol, Lorenz, Rössler and Hénon). Four groups were generated compu...

Modern Statistical Machine Translation (SMT) systems make their decisions based on multiple information sources, which assess various aspects of the match between a source sentence and its possible translation(s). Tuning a SMT system consists in finding the right balance between these sources so as to produce the best possible output, and is usually achieved through Minimum Error Rate Training ...

From the theory of Bayesian pattern recognition it is well known that the maximum a posteriori decision criterion yields a recogniser with the minimum probability of assigning the incorrect label to a pattern, if the correct probability distributions are used. This MAP criterion is also routinely employed in automatic speech recognition system. The problem addressed in this thesis is the fact t...

This paper discusses procedures for approximating high-order rational Dower spectrum matrices and minimum ~ h a s e stable transfer function matrices by lower-order objects of the same type. The basis of the approximation is to secure closeness of a high-order and low-order minimum phase stable transfer function matrix in phase, and to infer from this, closeness in magnitude. A suitable definit...

The authors present a new numerical method for the Chebyshev approximation of minimum phase FIR digital filters. This method is based on solving a least squares (LS) problem iteratively. At each iteration, the desired response is transformed so as to have an equiripple magnitude error. This method makes it possible to design minimum phase FIR filters whose magnitude error is quasi-equiripple. U...

The most commonly used method for training feature weights in statistical machine translation (SMT) systems is Och’s minimum error rate training (MERT) procedure. A well-known problemwith Och’s procedure is that it tends to be sensitive to small changes in the system, particularly when the number of features is large. In this paper, we quantify the stability of Och’s procedure by supplying diff...

The derivation and analysis of optimum multiuser detectors for additive-rate and additive-light Poisson multiple-access channels are studied. The observed point process models the output of an ideal photodetector illuminated by several synchronous or asynchronous users who modulate coherent light of the same frequency. Dynamic programmingbased decision rules for the asynchronous multiple-access...