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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control)
Mohammed Riyaz Ahmed
REVA University
Computer Science & IT Electrical & Electronics Engineering

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Design and development of learning model for compression and processing of deoxyribonucleic acid genome sequence Raveendra Gudodagi; Rayapur Venkata Siva Reddy; Mohammed Riyaz Ahmed
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1786-1794

Abstract

Owing to the substantial volume of human genome sequence data files (from 30-200 GB exposed) Genomic data compression has received considerable traction and storage costs are one of the major problems faced by genomics laboratories. This involves a modern technology of data compression that reduces not only the storage but also the reliability of the operation. There were few attempts to solve this problem independently of both hardware and software. A systematic analysis of associations between genes provides techniques for the recognition of operative connections among genes and their respective yields, as well as understandings into essential biological events that are most important for knowing health and disease phenotypes. This research proposes a reliable and efficient deep learning system for learning embedded projections to combine gene interactions and gene expression in prediction comparison of deep embeddings to strong baselines. In this paper we preform data processing operations and predict gene function, along with gene ontology reconstruction and predict the gene interaction. The three major steps of genomic data compression are extraction of data, storage of data, and retrieval of the data. Hence, we propose a deep learning based on computational optimization techniques which will be efficient in all the three stages of data compression.
Design and implementation of DA FIR filter for bio-inspired computing architecture B. U. V. Prashanth; Mohammed Riyaz Ahmed; Manjunath R. Kounte
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i2.pp1709-1718

Abstract

This paper elucidates the system construct of DA-FIR filter optimized for design of distributed arithmetic (DA) finite impulse response (FIR) filter and is based on architecture with tightly coupled co-processor based data processing units. With a series of look-up-table (LUT) accesses in order to emulate multiply and accumulate operations the constructed DA based FIR filter is implemented on FPGA. The very high speed integrated circuit hardware description language (VHDL) is used implement the proposed filter and the design is verified using simulation. This paper discusses two optimization algorithms and resulting optimizations are incorporated into LUT layer and architecture extractions. The proposed method offers an optimized design in the form of offers average miminimizations of the number of LUT, reduction in populated slices and gate minimization for DA-finite impulse response filter. This research paves a direction towards development of bio inspired computing architectures developed without logically intensive operations, obtaining the desired specifications with respect to performance, timing, and reliability.
Power saving and optimal hybrid precoding in millimeter wave massive MIMO systems for 5G Abdul Haq Nalband; Mrinal Sarvagy; Mohammed Riyaz Ahmed
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 6: December 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i6.15952

Abstract

The proliferation of wireless services emerging from use cases offifth-generation(5G) technology is posing many challenges on cellular communicationinfrastructure. They demand to connect a massive number of devices withenhanced data rates. The massive multiple-input multiple-output (MIMO)technology at millimeter-wave (mmWave) in combination with hybrid precodingemerges as a concrete tool to address the requirements of 5G networkdevelopments. But Massive MIMO systems consume significant power fornetwork operations. Hence the prior role is to improve the energy efficiency byreducing the power consumption. This paper presents the power optimizationmodels for massive MIMO systems considering perfect channel state information(CSI) and imperfect CSI. Further, this work proposes an optimal hybrid precodingsolution named extended simultaneous orthogonal matchingpursuit (ESOMP).Simulation results reveal that a constant sum-rate can be achieved in massiveMIMO systems while significantly reducing the power consumption. Theproposed extended SOMPhybrid precoder performsclose to the conventionaldigital beamforming method. Further, modulation schemes compatible withmassive MIMO systems are outlined and their bit error rate (BER) performance isinvestigated
Co-Authors Abdul Haq Nalband B. U. V. Prashanth Manjunath R. Kounte Mrinal Sarvagy Raveendra Gudodagi Rayapur Venkata Siva Reddy