VLSI Design and Implementation for Adaptive Filter using LMS Algorithm

Adaptive filters, as part of digital signal systems, have been widely used, as well as in applications such as adaptive noise cancellation, adaptive beam forming, channel equalization, and system identification. However, its implementation takes a great deal and becomes a very important field in digital system world. When FPGA (Field Programmable Logic Array) grows in area and provides a lot of facilities to the designers, it becomes an important competitor in the signal processing market. In general FIR structure has been used more successfully than IIR structure in adaptive filters. However, when the adaptive FIR filter was made this required appropriate algorithm to update the filter’s coefficients. The algorithm used to update the filter coefficient is the Least Mean Square (LMS) algorithm which is known for its simplification, low computational complexity, and better performance in different running environments. When compared to other algorithms used for implementing adaptive filters the LMS algorithm is seen to perform very well in terms of the number of iterations required for convergence. This phenomenon can be achieved by a sufficient choice of bit length to represent the filter’s coefficients. This paper presents a lowcost and high performance programmable digital finite impulse response (FIR) filter. It follows the adaptive algorithm used for the development of the system. The architecture employs the computation sharing algorithm to reduce the computation complexity

DESIGN OF NEURO-WAVELET BASED VECTOR QUANTIZER FOR IMAGE COMPRESSION

This paper presents a novel approach to design a vector quantizer for image compression. Compression of image data using Vector Quantization (VQ) will compare Training Vectors with Codebook that has been designed. The result is an index of position with minimum distortion. Moreover it provides a means of decomposition of the signal in an approach which takes the improvement of inter and intra band correlation as more lithe partition for higher dimension vector spaces. Thus, the image is compressed without any loss of information. It also provides a comparative study in the view of simplicity, storage space, robustness and transfer time of various vector quantization methods. In addition the proposed paper also presents a survey on different methods of vector quantization for image compression and application of SOFM

An Intelligent Method Based Medical Image Compression

Compression methods are important in many medical applications to ensure fast interactivity through large sets of images (e.g. volumetric data sets, image databases), for searching context dependant images and for quantitative analysis of measured data. Medical data are increasingly represented in digital form. The limitations in transmission bandwidth and storage space on one side and the growing size of image datasets on the other side has necessitated the need for efficient methods and tools for implementation. Many techniques for achieving data compression have been introduced. Wavelet transform techniques currently provide the most promising approach to high-quality image compression, which is essential for Teleradiology. This paper presents an approach of intelligent method to design a vector quantizer for image compression. The image is compressed without any loss of information. It also provides a comparative study in the view of simplicity, storage space, robustness and transfer time of various vector quantization methods. The proposed approach presents an efficient method of vector quantization for image compression and application of SOFM

ATHENA detector proposal - a totally hermetic electron nucleus apparatus proposed for IP6 at the Electron-Ion Collider

ATHENA has been designed as a general purpose detector capable of delivering the full scientific scope of the Electron-Ion Collider. Careful technology choices provide fine tracking and momentum resolution, high performance electromagnetic and hadronic calorimetry, hadron identification over a wide kinematic range, and near-complete hermeticity.This article describes the detector design and its expected performance in the most relevant physics channels. It includes an evaluation of detector technology choices, the technical challenges to realizing the detector and the R&D required to meet those challenges

ATHENA detector proposal — a totally hermetic electron nucleus apparatus proposed for IP6 at the Electron-Ion Collider

ATHENA has been designed as a general purpose detector capable of delivering the full scientific scope of the Electron-Ion Collider. Careful technology choices provide fine tracking and momentum resolution, high performance electromagnetic and hadronic calorimetry, hadron identification over a wide kinematic range, and near-complete hermeticity. This article describes the detector design and its expected performance in the most relevant physics channels. It includes an evaluation of detector technology choices, the technical challenges to realizing the detector and the R&D required to meet those challenges

DESIGN AND ANALYSIS OF MIMO SYSTEM FOR UWB COMMUNICATION

ABSTRACT Multiple transmit and receive antennas are used MIMO system. The system creates parallel MIMO subchannels to transmit independent streams of data under the appropriate channel conditions. Similarly, Ultrawideband (UWB) communication has attracted great interest for various applications in recent days. Spatially multiplexed (SM) multiple-input multiple-output (MIMO) systems gains the spectral efficiency as well as high data rates without consuming additional power, bandwidth or time slots. In this paper, we extend the concept of MIMO to UWB systems. The correlated channel for such purpose is considered and the performance has been analyzed for spatial multiplexing SM-UWB-MIMO system which is required for estimation. The system performance substantially degrades in the presence of high values of spatial correlation. To avoid the degradation of such system, it has been designed for virtual UWB-MIMO Time Reversal (TR) system, so that it is not affected by the transmit correlation. Another novel method to reduce the effect of correlation has been chosen by taking the Eigen value of the channel matrix for the computation of the system performance. The result shows its performance