Low-Complexity Methodology for Complex Square-Root Computation

Abstract : In this brief, we propose a low-complexity methodology to compute a complex square root using only a circular coordinate rotation digital computer (CORDIC) as opposed to the state-of-the-art techniques that need both circular as well as hyperbolic CORDICs. Subsequently, an architecture has been designed based on the proposed methodology and implemented on the ASIC platform using the UMC 180-nm Technology node with 1.0 V at 5 MHz. Field programmable gate array (FPGA) prototyping using Xilinx’ Virtex-6 (XC6v1x240t) has also been carried out. After thorough theoretical analysis and experimental validations, it can be inferred that the proposed methodology reduces 21.15% slice look up tables (on FPGA platform) and saves 20.25% silicon area overhead and decreases 19% power consumption (on ASIC platform) when compared with the state-of-the-art method without compromising the computational speed, throughput, and accuracy.
 EXISTING SYSTEM :
 ? In this, we will design one simple module (OR gate); however, in the future, you will be designing such modules and completing the overall circuit design from these existing files. ? Our aim is the elimination of the operation of calculating random values, in the state-of-the art section, we also discuss existing algorithms known as deterministic PSO (DPSO). ? In this paper we deal with digital implementation, it is more appropriate to take a closer look at existing solutions in digital technique. ? The modeling of the behavior of flocks of animals, e.g., ants or bees, it offers a good performance in problem solving tasks that require searching for a global optimum in situations where many local extrema exist.
 DISADVANTAGE :
 ? The industry has many optimization problems that require fast and effective computational algorithms which operate regardless of the size (dimensionality) of the solution space. ? To overcome this problem, in one of our former works, we proposed a circuit that can be used for this purpose. ? A significant problem here was how to determine optimal rules for the system operating during the flood period. ? The ability to implement the swarm algorithm in hardware is also useful in optimization problems that are computationally intensive or have nonlinear constraints.
 PROPOSED SYSTEM :
 • We proposed a low complexity methodology to compute the square root of a number and complex number using different modes available in CORDIC. • The purpose of this is to give new users an exposure to the basic and necessary steps to implement and examine your own designs using ISE environment. • In this work, we propose a novel metaheuristic algorithm that evolved from a conventional particle swarm optimization (PSO) algorithm for application in miniaturized devices and systems that require low energy consumption. • We proposed solutions that enable the development of low energy consumption miniature artificial neural networks in specialized integrated circuits realized in CMOS technology
 ADVANTAGE :
 ? These algorithms need to be enforced associate optimized in hardware therefore on modify them to handle real time data whereas maintaining associate optimum trade-off between fully totally different performance parameters (speed and power). ? Complex numbers have been used significantly in scientific community for the real-time data representation and system modeling, including electronic circuits, electromagnetism, communication systems, and signal processing algorithms. ? However, existing real valued square-root computation methods cannot be used directly to compute complex square root without requiring additional hardware.

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