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Experimental results show that a word-based arithmetic-coding scheme, a fractional-bit compression algorithm which is known to be time consuming, can achieve a higher compression performance for Chinese text. This article examines how to cascade the word-segmentation model with a faster alternative, the integral-bit compression algorithm. (Author/AEF)

A study examines rectangle packing problem using heuristics with respect to two-dimensional packing and cutting.

In the use of extended Kalman filter approach in training and pruning a feedforward neural network, one usually encounters the problems on how to set the initial condition and how to use the result obtained to prune a neural network. In this paper, some cues on the setting of the initial condition will be presented with a simple example illustrated. Then based on three assumptions - 1) the size of training set is large enough; 2) the training is able to converge; and 3) the trained network model is close to the actual one, an elegant equation linking the error sensitivity measure (the saliency) and the result obtained via extended Kalman filter is devised. The validity of the devised equation is then testified by a simulated example. Index Terms - Extended Kalman filter, multilayer perceptron, pruning training, weight saliency.

Recently we have proposed a simple circuit of winner-take-all (WTA) neural network. Assuming no external input, we have derived an analytic equation for its network response time. In this paper, we further analyze the network response time for a class of winner-take-all circuits involving self-decay and show that the network response time of such a class of WTA is the same as that of the simple WTA model. Index Terms - Inputless winner-take-all neural network, network response time, self-decay.

In this paper, the regularization of employing the forgetting recursive least square (FRLS) training technique on feedforward neural networks is studied. We derive our result from the corresponding equations for the expected prediction error and the expected training error. By comparing these error equations with other equations obtained previously from the weight decay method, we have found that the FRLS technique has an effect which is identical to that of using the simple weight decay method. This new finding suggests that the FRLS technique is another on-line approach for the realization of the weight decay effect. Besides, we have shown that, under certain conditions, both the model complexity and the expected prediction error of the model being trained by the FRLS technique are better than the one trained by the standard RLS method. Index Terms--Feedforward neural network, forgetting recursive least square, model complexity, prediction error, regularization, weight decay.

Explores a word-based arithmetic coding scheme for higher compression performance for Chinese text. Fractional-bit compression algorithm; Change in direction to study how to cascade the word segmentation model with the integral-bit compression algorithm; Objective to help practitioners of information retrieval to design word-based compression algorithms for Chinese.