Development of a New Transform:MRT

Fourier transform methods are employed heavily in digital signal processing. Discrete Fourier Transform (DFT) is among the most commonly used digital signal transforms. The exponential kernel of the DFT has the properties of symmetry and periodicity. Fast Fourier Transform (FFT) methods for fast DFT computation exploit these kernel properties in different ways. In this thesis, an approach of grouping data on the basis of the corresponding phase of the exponential kernel of the DFT is exploited to introduce a new digital signal transform, named the M-dimensional Real Transform (MRT), for l-D and 2-D signals. The new transform is developed using number theoretic principles as regards its specific features. A few properties of the transform are explored, and an inverse transform presented. A fundamental assumption is that the size of the input signal be even. The transform computation involves only real additions. The MRT is an integer-to-integer transform. There are two kinds of redundancy, complete redundancy & derived redundancy, in MRT. Redundancy is analyzed and removed to arrive at a more compact version called the Unique MRT (UMRT). l-D UMRT is a non-expansive transform for all signal sizes, while the 2-D UMRT is non-expansive for signal sizes that are powers of 2. The 2-D UMRT is applied in image processing applications like image compression and orientation analysis. The MRT & UMRT, being general transforms, will find potential applications in various fields of signal and image processing.

Development and Evaluation of Blind Identification Techniques for Nonlinear Systems

Identification and Control of Non‐linear dynamical systems are challenging problems to the control engineers.The topic is equally relevant in communication,weather prediction ,bio medical systems and even in social systems,where nonlinearity is an integral part of the system behavior.Most of the real world systems are nonlinear in nature and wide applications are there for nonlinear system identification/modeling.The basic approach in analyzing the nonlinear systems is to build a model from known behavior manifest in the form of system output.The problem of modeling boils down to computing a suitably parameterized model,representing the process.The parameters of the model are adjusted to optimize a performanace function,based on error between the given process output and identified process/model output.While the linear system identification is well established with many classical approaches,most of those methods cannot be directly applied for nonlinear system identification.The problem becomes more complex if the system is completely unknown but only the output time series is available.Blind recognition problem is the direct consequence of such a situation.The thesis concentrates on such problems.Capability of Artificial Neural Networks to approximate many nonlinear input-output maps makes it predominantly suitable for building a function for the identification of nonlinear systems,where only the time series is available.The literature is rich with a variety of algorithms to train the Neural Network model.A comprehensive study of the computation of the model parameters,using the different algorithms and the comparison among them to choose the best technique is still a demanding requirement from practical system designers,which is not available in a concise form in the literature.The thesis is thus an attempt to develop and evaluate some of the well known algorithms and propose some new techniques,in the context of Blind recognition of nonlinear systems.It also attempts to establish the relative merits and demerits of the different approaches.comprehensiveness is achieved in utilizing the benefits of well known evaluation techniques from statistics. The study concludes by providing the results of implementation of the currently available and modified versions and newly introduced techniques for nonlinear blind system modeling followed by a comparison of their performance.It is expected that,such comprehensive study and the comparison process can be of great relevance in many fields including chemical,electrical,biological,financial and weather data analysis.Further the results reported would be of immense help for practical system designers and analysts in selecting the most appropriate method based on the goodness of the model for the particular context.

An Approach Towards The Development Of An Efficient Symmetric Key Encryption Scheme

n the recent years protection of information in digital form is becoming more important. Image and video encryption has applications in various fields including Internet communications, multimedia systems, medical imaging, Tele-medicine and military communications. During storage as well as in transmission, the multimedia information is being exposed to unauthorized entities unless otherwise adequate security measures are built around the information system. There are many kinds of security threats during the transmission of vital classified information through insecure communication channels. Various encryption schemes are available today to deal with information security issues. Data encryption is widely used to protect sensitive data against the security threat in the form of “attack on confidentiality”. Secure transmission of information through insecure communication channels also requires encryption at the sending side and decryption at the receiving side. Encryption of large text message and image takes time before they can be transmitted, causing considerable delay in successive transmission of information in real-time. In order to minimize the latency, efficient encryption algorithms are needed. An encryption procedure with adequate security and high throughput is sought in multimedia encryption applications. Traditional symmetric key block ciphers like Data Encryption Standard (DES), Advanced Encryption Standard (AES) and Escrowed Encryption Standard (EES) are not efficient when the data size is large. With the availability of fast computing tools and communication networks at relatively lower costs today, these encryption standards appear to be not as fast as one would like. High throughput encryption and decryption are becoming increasingly important in the area of high-speed networking. Fast encryption algorithms are needed in these days for high-speed secure communication of multimedia data. It has been shown that public key algorithms are not a substitute for symmetric-key algorithms. Public key algorithms are slow, whereas symmetric key algorithms generally run much faster. Also, public key systems are vulnerable to chosen plaintext attack. In this research work, a fast symmetric key encryption scheme, entitled “Matrix Array Symmetric Key (MASK) encryption” based on matrix and array manipulations has been conceived and developed. Fast conversion has been achieved with the use of matrix table look-up substitution, array based transposition and circular shift operations that are performed in the algorithm. MASK encryption is a new concept in symmetric key cryptography. It employs matrix and array manipulation technique using secret information and data values. It is a block cipher operated on plain text message (or image) blocks of 128 bits using a secret key of size 128 bits producing cipher text message (or cipher image) blocks of the same size. This cipher has two advantages over traditional ciphers. First, the encryption and decryption procedures are much simpler, and consequently, much faster. Second, the key avalanche effect produced in the ciphertext output is better than that of AES.

Investigations on Metamaterial Based Spiral Inductors for Compact Microwave Devices

Division of Electronics Engineering

Re-Engineering Towed Arrays for Quality Enhancement - Network Based Towed Array

The Towed Array electronics is a multi-channel simultaneous real time high speed data acquisition system. Since its assembly is highly manpower intensive, the costs of arrays are prohibitive and therefore any attempt to reduce the manufacturing, assembly, testing and maintenance costs is a welcome proposition. The Network Based Towed Array is an innovative concept and its implementation has remarkably simplified the fabrication, assembly and testing and revolutionised the Towed Array scenario. The focus of this paper is to give a good insight into the Reliability aspects of Network Based Towed Array. A case study of the comparison between the conventional array and the network based towed array is also dealt with