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Pitak THUMWARIN Takenobu MATSUURA
In this paper, we propose an on-line writer recognition method for Thai numeral. A handwriting process is characterized by a change of numeral's shape, which is represented by two features, a displacement of pen-point position and an area of triangle determined from the two adjacent points of pen-point position and the origin. First, the above two features are expanded into Fourier series. Secondly, in order to describe feature of handwriting, FIR (Finite impulse response) system having the above Fourier coefficients as input and output of the system is introduced. The impulse response of the FIR system is used as the feature of handwriting. Furthermore, K-L expansion of the obtained impulse response is used to recognize writer. Writer recognition experiments are performed by using 3,770 data collected by 54 Thai writers for one year. The average of Type I (false rejection) error rate and Type II (false acceptance) error rate were 2.16% and 1.12%, respectively.
Mitsuru KAWAMOTO Yujiro INOUYE
The present paper deals with the blind deconvolution of a Multiple-Input Multiple-Output Finite Impulse Response (MIMO-FIR) system. To deal with the blind deconvolution problem using the second-order statistics (SOS) of the outputs, Hua and Tugnait considered it under the conditions that a) the FIR system is irreducible and b) the input signals are spatially uncorrelated and have distinct power spectra. In the present paper, the problem is considered under a weaker condition than the condition a). Namely, we assume that c) the FIR system is equalizable by means of the SOS of the outputs. Under b) and c), we show that the system can be blindly identified up to a permutation, a scaling, and a delay using the SOS of the outputs. Moreover, based on this identifiability, we show a novel necessary and sufficiently condition for solving the blind deconvolution problem, and then, based on the condition, we propose a new algorithm for finding an equalizer using the SOS of the outputs, while Hua and Tugnait have not proposed any algorithm for solving the blind deconvolution under the conditions a) and b).