This paper presents a novel biometric watermarking algorithm for improving the recognition accuracy and protecting the face and fingerprint images from tampering. Multi-resolution Discrete Wavelet Transform is used for embedding the face image in a fingerprint image. An intelligent learning algorithm based on υ-Support Vector Machine (SVM) is introduced to enhance the quality of the extracted face image. The performance of the watermarking algorithm is experimentally validated using existing fingerprint and face recognition algorithms. The results show that the extracted fingerprint and face images are of high quality. The use of SVM enhances the performance of face recognition by at least 10% even when the watermarked image is subjected to certain geometric and frequency attacks such as scaling, cropping, compression and filtering.

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Controlling chaos signal patterns at 12GHz was demonstrated on the resonant tunneling chaos generator circuit. This was made possible by implementing the reset switch, which resets the circuit to various initial conditions periodically. The reset period was set so short that the initial condition errors can not grow significantly. Thus the circuit repeated identical signal patterns, and they can be clearly observed by a sampling oscilloscope. The application of this circuit to fabricate ultrahigh speed pulse pattern generator was also discussed in this paper.

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An approach for the analysis of dispersive media, based on a special transmission-line modelling method with symmetrical condensed node (TLM-SCN) with voltage sources, is proposed. It is used in the case of linear and isotropic Lorentz frequency dependence media. The scattering matrix of the proposed SCN is provided and the efficiency and the validity of this approach are proved by the computation of the reflection coefficients of air-Lorentz medium interfaces and the RCS of a dispersive sphere.

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