Browsing by Author "Zakaria, Hatem M."

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Design of an Asynchronous Switch for Clock Domain Crossing Interfaces
(2019-04) Zakaria, Hatem M.; Mohamed Ali, Ashraf; Elnahel, Waleed
This paper proposes a design of an asynchronous switch interfacing circuit between any numbers of different local clock synchronous domains. The asynchronous switch will generate a slower clock frequency from different local clock modules and moderate the high rated clock domain to slow down its clock frequency without stopping or pausing any clock of them during the data communication phase. The proposed design is implemented using the CMOS 45nm technology of STMicroelectronics and simulated using timed VHDL model (Xilinx ISE Design Suite 12.1). The delay time is required to change the clock frequency is mathematically modeled. It is shown that the switching delay time depends on the number of multipoint communicating domains. The proposed system is designed to use a small number of circuit elements that results in conspicuous improvements in terms of power consumption, throughput, and circuit area
A Modified Hilbert Analysis Method to Improve Voice Stress Analysis Systems
(International Journal of Computer Applications (0975 – 8887), 2019-05) El Nahal, Waleed; Mohamed Ali, Ashraf; Zakaria, Hatem M.
Analyzing the cognitive load generated in the brain is the most important issue for specific applications such as voice stress analysis (VSA) systems in which the detection of stressed speech caused by an act of deception under law enforcement interview questioning or military interrogation. The most widely used algorithm for VSA systems is the empirical mode decomposition (EMD). Currently EMD that uses the cubic spline interpolation technique to find the envelopes of the non-periodic signal takes a long processing time, and to achieve accurate results the process is very time consuming and expensive otherwise some tests tend to produce inaccurate results. On the other hand EMD that uses Hilbert analysis method to speed up the process and provide more accurate results, suffer from finding the envelopes of the non-periodic signal. In this paper, a new algorithm is proposed for VSA, named fast Fourier transform (FFT) with a modified Hilbert analysis method (MH) for EMD algorithm, (FTT_MH_EMD), which provides a new technique that modifies the conventional Hilbert analysis method and combines it with the fast Fourier transform algorithm to overcome the previous limitations of using individually the FTT algorithm, the cubic spline interpolation technique or the conventional Hilbert analysis method and that can speed up the processing time and gives accurate results. Simulations and results witness that the proposed algorithm provides higher accuracy than the other attempts and also the processing time has dropped by 10 times faster than those in the products currently available in the market for VSA The advantages of using FFT for VSA are low cost when implemented in products and fast iterations method, and the disadvantage is the low resolution and therefore low accuracy (60%–70%) [1]. On the other hand the advantage of using Mcquiston Ford for VSA is the high accuracy results which are greater than 80%, and the disadvantage are complex algorithms and expensive implementation [5]. An important, barely audible, frequency is produced by the human vocal cords which could measure in a fairly accurate manner if the subject is being deceitful due to the effect the brain’s cognitive load has on the vocal cords [1 and 5]. This frequency is called the micro-tremor frequency generated by the involuntary micro-tremor muscle fibers in the vocal cords. When the subject is being deceitful, more work is induced on the brain which as a result causes tremor muscles to tense up in a non-voluntary manner [1 and 6]. Different non voluntary muscles would tense up including the micro-tremor muscle fibers found on the vocal cords. This induces a higher micro-tremor frequency range notably showing a large quantity of induced cognitive load and therefore a deceitful subject [7]. The micro-tremor frequency of all muscles in the body, including the vocal chords, vibrates in the 8 to 12 Hz range in the normal case without any stress, and that the VSA vendors claim to be the sole source of detecting if an individual is lying or is under stress [1, 4 and 8]. The paper is organized from seven sections EMD, EMD with Hilbert Analysis, previous work and limitations, the proposed algorithm, the proposed VSA system model, results and simulations and finally the conclusion
VLSI Architecture for Optimization Transform Technique based on Compression of ECG Signals
(2019-04) El Nahal, Waleed; Mohamed Ali, Ashraf; Zakaria, Hatem M.
The measurement of electrical activity of the heart via electrodes is named as Electrocardiography (ECG). An efficient compression technique using the compressive sensing method is required. Compressive Sensing (CS) holds the promise to be a key for acquisition and reconstruction of sparse signals. The reconstruction of such signals makes sampling rates below Nyquist rate. In this work, a novel framework was proposed that is based on the idea of CS theory for the compression of mother and fetal heart beats. The proposed scheme is based on the sparse representation of the components derived from the curvelet transform of the original Electrocardiogram (ECG) signal. The ECG signals may be approximated by a few coefficients that can be taken from a wavelet basis. This fact allows a compressed sensing approach for ECG signal compression to be introduced and to be a domain of search. ECG signals illustrate redundancy between adjacent heart beats. This redundancy implies a high fraction of common support between consecutive heart beats. The main contribution of this paper lies in the using of curvelet transform in order to generate sparsity in ECG signal. This transformation is considered an excellent approach as illustrated in this paper. Simulation results represent a better approach than Discrete Wavelet Transform (DWT) that is based on compression of ECG. MIT-BIH database is used for experimentation. The MIT-BIH database contains different kinds of ECG signals that include both abnormal ECG and normal ECG, which have different sampling rates. MATLAB tool is used for simulation purpose. The novelty of the method is that the Compression Ratio (CR) achieved by detail coefficients is better. The performance measure of the reconstructed signal is carried out by Percentage Root Mean Difference (PRD). This paper also introduces the efficient realization of the different transformation techniques using FPGA. Thus the contribution of this paper lies into two main parts. The first part is specialized in determining the proper transformation that is used in the compression of ECG signals. The second part of the contribution is summarized in using suitable hardware to implement this design. Architecture can be based on the ideas of parallelism and pipelining to get the minimum throughput and speed. Architecture is cascade and simple for calculating curvelet coefficients. The reduction of the memory size can be done by splitting ROM table. The description and functionalities of the design are modeled by Verilog HDL. The simulation and synthesis methodology are used on Virtex-II Pro FPGA that uses less number of resources of the FPGA.