Volume-1 Issue-2, May 2021 – Indian Journal of Signal Processing (IJSP)

B1005041221

IJSP Journal — Tue, 10 Aug 2021 12:07:25 +0000

The Indian Journal of Signal Processing (IJSP) has ISSN 2582-8320 (online), open-access, peer-reviewed, periodical quarterly international journal, which is published by Lattice Science Publication (LSP) in February, May, August and November. The aim of the journal is to publish high quality peer–reviewed original articles in the area of Signal Processing that covers Analog Filter Design, Applications of Fourier Transforms, Coding Theory, Continuous Time Signals, Digital Communication Techniques, Digital Design and Synthesis, Digital Filter Structure, Digital Systems – Characterization, Description and Testing, Discrete Fourier Transform, DSP Algorithms and Architecture, IR Filters, IIR Filters, Linear Algebra for Signal Processing, Linear and Nonlinear Optimization, Multirate Signal Processing, Optical, Signal Processing, Random Processes, Signal Compression-Theory and Methods, Simple Digital Filters, Speech and Audio Processing, Wavelet Theory, Filter Design and Structures, Fast Algorithms, Adaptive filters, Nonlinear Signals and Systems, Multirate Filtering and Filter Banks, Signal Reconstruction, Time-Frequency Analysis, Spectral Estimation, Higher Order Spectrum Analysis, Parameter Estimation, Detection, Array Signal Processing, Statistical Signal Analysis, Signal and System Modelling, Cyclostationary Signal Analysis, Speech Production and Perception, Speech Analysis, Speech Synthesis, Speech Coding, Speech Recognition, Speech Enhancement and Noise Reduction, Active Noise Control, Active Noise Reduction, Echo Cancellation, Psychoacoustics, Broadband Audio Coding, Signal Processing for Music, Binaural Systems, Room Acoustics, Digital Transforms, HDTV, Multidimensional Systems, Machine Vision, Image Coding, Image Motion / Sequence / Video, Computed Imaging, Geophysical and Seismic Processing, Image Analysis and Segmentation, Image Filtering, Restoration and Enhancement, Image Representation and Modelling, Pattern Recognition, Neural Networks, Fuzzy Systems, Evolutionary Computation, Expert Systems, Multisensor Data Fusion, Architectures and VLSI Hardware, Programmable Signal Processors, Algorithms and Applications Mappings, Design Methology and CAD Tools, Languages and Real Time Software, Real Time System Estimation, Optimization Problems in Signal Processing, Radar, Sonar, Biomedical Processing, Geophysical Signal Processing, Underwater Signal Processing, Remote Sensing, Robotics, Astronomy, Classification, Crime on the Web, Security/Publicity/Privacy/Reputation, Frauds in Business Reputation, Satellite Signals Processing, Measure and Instrumentation. #Analog Filter Design #Applications of Fourier Transforms #Coding Theory #Continuous Time Signals #Digital Communication Techniques #Digital Design and Synthesis #Digital Filter Structure #Digital Systems – Characterization #Description and Testing #Discrete Fourier Transform #DSP Algorithms and Architecture #IR Filters #IIR Filters #Linear Algebra for Signal Processing #Linear and Nonlinear Optimization #Multirate Signal Processing #Neural Networks #Optical #Signal Processing #Random Processes #Signal Compression-Theory and Methods #Simple Digital Filters #Speech and Audio Processing #Wavelet Theory #Filter Design and Structures #Fast Algorithms #Adaptive filters #Nonlinear Signals and Systems #Multirate Filtering and Filter Banks #Signal Reconstruction #Time-Frequency Analysis #Spectral Estimation #Higher Order Spectrum Analysis #Parameter Estimation #Detection #Array Signal Processing #Statistical Signal Analysis #Signal and System Modelling #Cyclostationary Signal Analysis #Speech Production and Perception #Speech Analysis #Speech Synthesis #Speech Coding #Speech Recognition #Speech Enhancement and Noise Reduction #Active Noise Control #Active Noise Reduction #Echo Cancellation #Psychoacoustics #Broadband Audio Coding #Signal Processing for Music #Binaural Systems #Room Acoustics #Digital Transforms #HDTV #Multidimensional Systems #Machine Vision #Image Coding #Image Motion / Sequence / Video #Computed Imaging #Geophysical and Seismic Processing #Image Analysis and Segmentation #Image Filtering #Restoration and Enhancement #Image Representation and Modelling #Pattern Recognition #Neural Networks #Fuzzy Systems #Evolutionary Computation #Expert Systems #Multisensor Data Fusion #Architectures and VLSI Hardware #Programmable Signal Processors #Algorithms and Applications Mappings #Design Methology and CAD Tools #Languages and Real Time Software #Real Time System Estimation #Optimization Problems in Signal Processing #Radar #Sonar #Biomedical Processing #Geophysical Signal Processing #Underwater Signal Processing #Remote Sensing #Robotics #Astronomy #Classification #Crime on the Web #Security/Publicity/Privacy/Reputation #Frauds in Business Reputation #Satellite Signals Processing #Measure and Instrumentation #PhD #Academic #Scopus #SCI #LatticeScience #Springer, #ScienceDirect #IEEE #Mendeley #Research #Scholarship #UGC #SSRN #LatticeScience #ESCI #Science #Journal #Conference #SSRN #PubLons

ECG Denoising Methodology using Intrinsic Time Scale Decomposition and Adaptive Switching Mean Filter
B.T. Krishna¹, P.S.Kameswari²
¹Dr Battula Tirumala Krishna, Professor, Department of Electronics and Communication Engineering JNTUK Kakinada, India.

²Putti Siva Kameswaari, M.Tech, Deaprtment Electronics and Communication Engineering, JNTUK Kakinada, India.

Manuscript received on 01 March 2021 | Revised Manuscript received on 06 March 2021 | Manuscript Accepted on 15 May 2021 | Manuscript published on 30 May 2021 | PP: 7-12 | Volume-1 Issue-2, May 2021 | Retrieval Number: 100.1/ijsp.B1005041221 | DOI: 10.54105/ijsp.B1005.051221

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© The Authors. Published by Lattice Science Publication (LSP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Electrocardiogram (ECG) is a widely employed tool for the analysis of cardiac disorders. A clean ECG is often desired for proper treatment of cardiac ailments. However, in the real scenario, ECG signals are corrupted with various noises during acquisition and transmission. In this article, an efficient ECG de-noising methodology using combined intrinsic time scale decomposition (ITD) and adaptive switching mean filter (ASMF) is proposed. The standard performance metric namely output SNR improvement measure the efficacy of the proposed technique at various signal to noise ratio (SNR). The proposed de-noising methodology is compared with other existing ECG de-noising approaches. A detail qualitative and quantitative study and analysis indicate that the proposed technique can be used as an effective tool for de-noising of ECG signals and hence can serve for better diagnostic in computer-based automated medical system. The performance of the proposed work is compared with existing ECG de-noising techniques namely wavelet soft thresholding based filter (DWT) [16], EMD with DWT technique [18], DWT with ADTF technique [19]. The effectiveness of the presented work has been evaluated in both qualitative and quantitative analysis. All the simulations are carried out using MATLAB software environment.

Keywords: Adaptive Switching Mean Filter, Electrocardiogram, Intrinsic Time Scale Decomposition, Signal to Noise Ratio.
Scope of the Article: Signal Processing

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B1004041221

IJSP Journal — Tue, 10 Aug 2021 12:01:26 +0000

A Flux Controlled Memristor using 90nm Technology
B.T.Krishna¹, Shaik. Mohaseena Salma²
¹B.T.Krishna, Electronics and Communication Engineering, JNTU Kakinada University, Kakinada (Andhra Pradesh), India.

²Shaik. mohaseena Salma, Electronics and Communication Engineering, JNTU Kakinada University, Kakinada (Andhra Pradesh), India.

Manuscript received on 01 March 2021 | Revised Manuscript received on 06 March 2021 | Manuscript Accepted on 15 May 2021 | Manuscript published on 30 May 2021 | PP: 1-6 | Volume-1 Issue-2, May 2021 | Retrieval Number: 100.1/ijsp.B1004041221 | DOI: 10.54105/ijsp.B1004.051221

Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Published by Lattice Science Publication (LSP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: A flux-controlled memristor using complementary metal–oxide–(CMOS) structure is presented in this study. The proposed circuit provides higher power efficiency, less static power dissipation, lesser area, and can also reduce the power supply by using CMOS 90nm technology. The circuit is implemented based on the use of a second-generation current conveyor circuit (CCII) and operational transconductance amplifier (OTA) with few passive elements. The proposed circuit uses a current-mode approach which improves the high frequency performance. The reduction of a power supply is a crucial aspect to decrease the power consumption in VLSI. An offered emulator in this proposed circuit is made to operate incremental and decremental configurations well up to 26.3 MHZ in cadence virtuoso platform gpdk using 90nm CMOS technology. proposed memristor circuit has very little static power dissipation when operating with ±1V supply. Transient analysis, memductance analysis, and dc analysis simulations are verified practically with the Experimental demonstration by using ideal memristor made up of ICs AD844AN and CA3080, using multisim which exhibits theoretical simulation are verified and discussed.

Keywords: current mode, memristor, emulator, pinched hysteresis loop, current conveyor (CCII), operational transconductance amplifier (OTA).
Scope of the Article: Signal Processing

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