Floating Point Unit is one of the integral unit in the Advanced Processors. The arithmetic operations on floating point unit are quite complicated. They are represented in IEEE 754 format in either 32-bit format (single precision) or 64-bit format (double precision). They are extensively used in high end processors for various applications such as mathematical analysis and formulation, signal processing etc. This paper describes the detailed process for the computation of addition, subtraction and multiplication operations on floating point numbers. It has been designed using VHDL. The design has been simulated and synthesized to identify the area occupied and its performance in terms of delay.

Abstract-Electrocardiogram (ECG) is very crucial and important tool to detect the cardiac problems. For ECG analysis, it is essential to measure ECG parameter accurately. It is very critical in all types of ECG application. The accurate R Peaks detection is starting step in extracting ECG features which is necessary for the other ECG performance stages. It is very essential to detect these R-peaks accurately and efficiently to detect heart diseases or anomalies which create primary source of death in the universe. Hence automatic R-peaks detection in a lengthy duration ECG signal is very meaningful to diagnose the cardiac disorders. Here a latest R-peak exposure algorithm depended on Shannon energy envelope estimator and logic to find peaks has been proposed which uses the simple threshold of Shannon energy.

ECG is very crucial and important tool to detect the cardiac problems. It has all the information related to the electrical activities of heart. This also has the information of normal and abnormal activities for the detection of the diseases. So it is essential and important to detect the accurate R-peaks in QRS complex, especially when the results are to be used for clinical applications. Hence in a long-term ECG signal, automatic R-peaks detection is very essential to diagnose cardiac disorders. In this paper we proposed a robust technique to detect R-peak which uses Wavelet Transform. The proposed R Peak detector is consists of a wavelet filter banks, a noise detector with zero-crossing points, multi-scaled product algorithm and soft-threshold algorithm.

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