are selected in such a way that they result in a minimal hardware overhead while embedding a unique signature that is difficult to remove and forge. Techniques are applicable in conjunction with an arbitrary behavioral synthesis task such as scheduling, assignment, allocation, transformation, and template

the components of the synthesized sound. Given one or more sound scenes, we provide well-defined means to: (1) identify points of interest in the sound and extract them into reusable templates, (2) transform sound components independently of the background or other events, (3) continually re

of their reflections (i.e. approx-imations) in the chosen language. The most important issues in this induction process are: – construction of relevant primitive concepts from which approximations of more complex concepts are assembled, – measures of inclusion and similarity (closeness) on concepts, – construction

of English writing style. Still these algorithms have not been tested for complete characters of English Alphabet. Hence, a system is required which can handle all classes of English text and identify characters among these classes. Keywords-OCR, templates, english-alphabets, alpha-numerics I. INTRODUCTION

First, I would like to thank to Dimka Karastoyanova and Mariano Cilia for all the fruitful discussions, their guidance and support through the course of this project. Thanks also to Prof. Alejandro Buchmann who sponsored my stay at Technische Universität Darmstadt during the spring of 2004. The special thanks go to my advisor, Mariano Cilia, who has made all this possible. Finally, I’d like to thank to my family for all these years of support.

. We develop a new theoretical framework to analyze this extreme case and develop new algorithms for signal reconstruction from such coarsely quantized measurements. The 1-bit CS framework leads us to scenarios where it may be more appropriate to reduce bit-depth instead of sampling rate. We find