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The advantage of RTR systems usually comes with some costs. The required time to map some areas of a program to an FPGA is considerable and affects the performance of RTR systems. Several methods have been developed to speed up the configuration process in these systems. Configuration compression can reduce the total number of write operations to load a(More)
A holistic system for the recognition of handwritten Farsi/Arabic words using right}left discrete hidden Markov models (HMM) and Kohonen self-organizing vector quantization is presented. The histogram of chain-code directions of the image strips, scanned from right to left by a sliding window, is used as feature vectors. The neighborhood information(More)
This paper presents a fuzzy hybrid learning algorithm (FHLA) for the radial basis function neural network (RBFNN). The method determines the number of hidden neurons in the RBFNN structure by using cluster validity indices with majority rule while the characteristics of the hidden neurons are initialized based on advanced fuzzy clustering. The FHLA combines(More)
This paper introduces a novel method for the recognition of human faces in digital images using a new feature extraction method that combines the global and local information in frontal view of facial images. Radial basis function (RBF) neural network with a hybrid learning algorithm (HLA) has been used as a classifier. The proposed feature extraction(More)
A technique for extracting filled-in information in form documents is presented. The transformation that is required to convert a filled-in form to match the master (blank form) is derived using results from projective geometry. Experimental studies with several forms indicate the proposed technique to be accurate and robust.