Mallika De

A new network topology with multiple meshes

This paper introduces a new network topology, called Multi-Mesh (MM), which uses multiple meshes as the basic building blocks interconnected in a suitable manner. The proposed network consists of n/sup 4/ processors and is 4-regular with a diameter of 2n. The network also contains a Hamiltonian cycle. Simple routing algorithms for point-to-point communication, one-to-all broadcast, and multicast have been described for this network. It is shown that a simple n/sup 2//spl times/n/sup 2/ mesh can also be emulated on this network in O(1) time. Several application examples have been discussed for which this network is found to be more efficient with regard to computational time than the corresponding mesh with the same number of processors. As examples, O(n) time algorithms for finding the sum, average, minimum, and maximum of n/sup 4/ data values, located at n/sup 4/ different processors have been discussed. Time-efficient implementations of algorithms for solving nontrivial problems, e.g., Lagranges interpolation, matrix transposition, matrix multiplication, and Discrete Fourier Transform (DFT) computation have also been discussed. The time complexity of Lagranges interpolation on this network is O(n) for n/sup 2/ data points compared to O(n/sup 2/) time on mesh of the same size. Matrix transpose requires O(n/sup 0.5/) time for an n/spl times/n. matrix. The time for multiplying two n/spl times/n matrices is O(n/sup 0.6/) with an AT-cost of O(n/sup 3/). DFT of n sample points can be computed in O(n/sup 0.6/) time on this network. The previous papers show that n/sup 4/ data elements can be sorted on this network in O(n) time.

An efficient sorting algorithm on the multi-mesh network

The shear-sort algorithm on an SIMD mesh model requires 4/spl radic/N+o(/spl radic/N) time for sorting N elements arranged on a /spl radic/N/spl times//spl radic/N mesh. In this paper, we present an algorithm for sorting N elements in time O(N/sup 1/4/) on an SIMD multi-mesh architecture, thereby significantly improving the order of the time complexity. The multi-mesh architecture is built around n/sup 2/ blocks, where each block is an n/spl times/n mesh with n=N/sup 1/4/, so that each processor will uniformly have four neighbors in the final topology.

Fast parallel algorithm for ternary multiplication using multivalued I/sup 2/L technology

Presents an algorithm for parallel multiplication of two n-bit ternary numbers. This algorithm uses the technique of column compression and computes the product in (2 upper bound /spl lsqb/log/sub 2/n/spl rsqb/+2) units of addition time of a single-bit ternary full adder. This algorithm requires regular interconnection between any two types of cells and hence is very suitable for VLSI implementation. The same algorithm is also applicable to the multiplication of negative numbers. >

Image recognition and processing using Artificial Neural Network

There are several techniques for image recognition. Among those methods, application of soft computing models on digital image has been considered to be an approach for a better result. The main objective of the present work is to provide a new approach for image recognition using Artificial Neural Networks. Initially an original gray scale intensity image has been taken for transformation. The Input image has been added with Salt and Peeper noise. Adaptive median Filter has been applied on noisy image such that the noise can be removed and the output image would be considered as filtered Image. The estimated Error and average error of the values stored in filtered image matrix have been calculated with reference to the values stored in original data matrix for the purpose of checking of proper noise removal. Now each pixel data has been converted into binary number (8 bit) from decimal values. A set of four pixels has been taken together to form a new binary number with 32 bits and it has been converted into a decimal. This process continues to produce new data matrix with new different set of values. This data matrix has been taken as original data matrix and saved in data bank. Now for recognition, a new test image has been taken and the same steps as salt & pepper noise insertion, removal of noise using adaptive median filter as mentioned earlier have been applied to get a new test matrix. Now the average error of the second image with respect to original image has been calculated based on the both generated matrices. If the average error is more than 45% then a conclusion can be made that the images are different and cannot be matched. But if the value of average error has been found to be less than or equal to 45%, an effort has been made to use the artificial neural network on test data matrix with reference to original data matrix thereby producing a new matrix of the second image(test image). The total average error has been calculated on generated data matrix produced after the application of artificial neural networks on test data matrix to check whether proper identification can be made or not. It has been observed that the value of average error is less than that of test image without application of artificial neural network. Further it has been observed that the test image is matching and recognized with respect to original image.

A novel hybrid approach to enhance low resolution images using particle swarm optimization

Enhancement of low resolution images is always a priority Enhancement of low resolution images is always a priority field of digital image processing. In this paper, we propose a novel hybrid approach based on discrete wavelet transform (DWT) and particle swarm optimization (PSO). To develop the proposed method we use spatial domain as well as frequency domain. To reduce the low frequencies from the input image we use the frequency domain. DWT is used to decompose the input low resolution image into different sub bands. Each of the interpolated high frequency sub band (LH, HL, HH) is then summed up with the interpolated output image of the frequency domain. In order to achieve high resolution image, the estimated high frequency sub bands of the intermediate stage and the interpolated low resolution input image have been combined by using inverse DWT. To generate a better high resolution image particle swarm optimization (PSO) technique has been used. The quantitative (root mean square error, normalized cross correlation, normalized absolute error) and visual outcome show the strength of this proposed method.

A comparative study on the performance of fuzzy logic, Bayesian logic and neural network towards decision-making

Soft computing models play an important role in the field of recognition, classification, data prediction, etc., and also in various application fields towards decision-making. Soft computing models include fuzzy logic, neural, network, genetic algorithm, particle swarm optimisation, tabu search, harmonie search, clustering, etc. The performance of a particular soft computing model can be ascertained using a particular dataset for the purpose of decision-making. Here, an effort has been made to make a comparison on the performance of fuzzy logic, Bayesian logic and neural network. The model with minimum error has been given preference for selection towards decision-making of information. The same method has been cross-checked based on the residual analysis to verify the earlier proposed observation. The said models have also been cross-checked based on other dataset. Under neural network, perceptron neural network model has been used.

A novel hybrid approach to restore historical degraded documents

Old degraded historical documents carry various important information regarding our culture, economics etc. proper restoration of these documents is very necessary. After digitization of these documents there remain noises and other low resolution components. These affect the overall visual appearance of the documents. In this paper a novel approach is proposed to enhance ancient historical documents. To enhance these digital format documents a two way approach is considered. At first Particle Swarm Optimization (PSO) and bilateral filter is applied. At second level Non-Linear Enhancement with bilateral filter is applied. Both the approaches are then tested visually and quantitively to show the effectiveness of the approach.

String graphixification based asymmetric key cryptographic algorithm using proposed concepts of GDC and S-loop matrix

The paper emphasizes on the effort of using the concept of gears and their distinguished genre in producing a unique technique for secured data transfer over a network. Gears have a major significance in diurnal strife of human existence. The driving force, rather more significantly the endeavor was to ensure and justify the importance of gears in the field of Cryptography and stamp its foundation via proposal of a unique methodology. The proposed technique is well-suited in finding its usage in any sector where secured data transfer is a must. The essence of the work adhered and its allied modality, confirms the ultimate target aimed at and the path conjured to attain it eventually.

Logarithmic Formula Generated Seed Based Cryptographic Technique using proposed Alphanumeric Number System and Rubik Rotation Algorithm

The work presents the manner in which the Logarithmic Formula Generated Seed Based Cryptographic Technique [LFGSCT] (de)ciphers the fragmented plain text, maintaining certain modus operandi. The model formulation of the proposed technique has been conceptualized and devised to generate arbitrary sequence of characters, in order to engender the seed using the generated logarithmic formula. The impetus following seed generation is encryption of the actual text based on the proposed Alphanumeric Number System [ANS]. Portraying in a nutshell would emphasize that the actual text has been divided into blocks of ten characters, ordered by the proposed number system. After the fragmentation, the encryption technique continues with the use of the generated seed, followed by the proposed Rubik Rotation Algorithm [RRA], and engaged to randomize the encrypted text. The concept fundamentally embodies the crispness of the proposed technique. During the decryption technique, the seed is retrieved from the cipher text, and an effortless backtracking logic is pursued to restore the actual text. The proposed methodology can be used with utmost ease for both encryption and decryption of any text at disposal. The proposed methodology will ensure immense use during encryption of emails, which is enormously important as well as significant in data transfer and network security.

Fast Parallel Multiplication Using Redundant Quarternary Number System

In this paper, we propose a high-speed VLSI multiplication scheme using redundant radix-4 representation of numbers. For m-digit by m-digit redundant radix-4 integer multiplication, we first generate m partial products, each of (m+1) digits in redundant radix-4 (RR-4) number system. These partial products are then added up four at a time by means of redundant quarternary adders. Parallel addition of four (m+1)-digit redundant radix-4 numbers can be performed in a constant time independent of m without any carry propagation. With these adders, multiplication of two m-digit numbers in RR-4 number system can be performed in ⌈(1/2)log2 m ⌉ + 1 steps of such additions of four RR-4 numbers. The number of computational elements of an m-digit multiplier based on the proposed algorithm is O(m2). Since the multiplier has a regular cellular array structure, it is suitable for VLSI implementation with O(m2 log m) AT-value.