Showing 4 results for Sharma
M. Sharma, K. P. Vittal,
Volume 6, Issue 4 (December 2010)
Abstract
The recent trends in electrical power distribution system operation and management are aimed at improving system conditions in order to render good service to the customer. The reforms in distribution sector have given major scope for employment of distributed generation (DG) resources which will boost the system performance. This paper proposes a heuristic technique for allocation of distribution generation source in a distribution system. The allocation is determined based on overall improvement in network performance parameters like reduction in system losses, improvement in voltage stability, improvement in voltage profile. The proposed Network Performance Enhancement Index (NPEI) along with the heuristic rules facilitate determination of feasible location and corresponding capacity of DG source. The developed approach is tested with different test systems to ascertain its effectiveness.
C. S. Vinitha, R. K. Sharma,
Volume 15, Issue 4 (December 2019)
Abstract
An efficient Lookup Table (LUT) design for memory-based multiplier is proposed. This multiplier can be preferred in DSP computation where one of the inputs, which is filter coefficient to the multiplier, is fixed. In this design, all possible product terms of input multiplicand with the fixed coefficient are stored directly in memory. In contrast to an earlier proposition Odd Multiple Storage (OMS), we have proposed utilizing Even Multiple Storage (EMS) scheme for memory-based multiplication and by doing so we are able to achieve a less complex and high-speed design. Because of the very simpler control circuit used in our design, to extract the odd multiples of the product term, we are also able to achieve a significant reduction in path delay and area complexity. For validation, the proposed design of the multiplier is coded in VHDL, simulated and synthesized using Xilinx tool and then implemented in Virtex 7 XC7vx330tffg1157 FPGA. Various key performance metrics like number of slices, number of slice LUT’s and maximum combinational path delay is estimated for different input word length. Also, the performance metrics are compared with the existing OMS design. It is found that the proposed EMS design occupies nearly 62% less area in terms of number of slices as compared to the OMS design and the maximum path delay is decreased by 77% for a 64-bit input. Further, the proposed multipliers are used in Transposed FIR filter and its performance is compared with the OMS multiplier based filter for various filter orders and various input lengths.
S. Juneja, R. Sharma,
Volume 15, Issue 4 (December 2019)
Abstract
Design of Global Positioning System (GPS) receiver with a low noise amplifier (LNA) in the front end remains a major design requirement for the success of modern day navigation and communication system. Any LNA is expected to meet the requirements like its ability to add the least amount of noise while providing sufficient gain, perfect input and output matching, and high linearity. However, most of the reported designs of LNAs present the need for striking a trade-off between these design parameters in order to obtain the desired performance for a particular RF receiver. This paper presents high gain (21dB), high input matched (-29dB), high reverse isolation (-41dB) and low noise figure (< 2dB) narrowband LNA for extremely low power level GPS L1 band signals broadcasting at 1.57GHz with a channel bandwidth of 10MHz. Inductive source degeneration topology is employed for the design and all the matching inductors in the circuit are used with fixed quality factor (Q) to model the losses for better tuning and matching. The design is carried out on Cadence Virtuoso Tool version IC6.1.6 and Spectre version MMSIM13.1 at 0.18µm technology node using a generic process development kit. Detailed mathematical analysis of the design is done and all the DC parameters like values of transconductance, gate source capacitance, drain source voltage, drain current, etc. are reported. Graphical analysis using Smith chart is carried out to present the results and to bring forth the trade-offs involved in the design. LNA draws 5mA current from 1.2V supply voltage and offers good linearity that is sufficient for GPS application and is measured by input intercept point 3 (IIP3 < ‑4dBm).
Biswapriyo Sen, Maharishi Kashyap, Jitendra Singh Tamang, Sital Sharma, Rijhi Dey,
Volume 20, Issue 2 (June 2024)
Abstract
Cardiovascular arrhythmia is indeed one of the most prevalent cardiac issues globally. In this paper, the primary objective was to develop and evaluate an automated classification system. This system utilizes a comprehensive database of electro- cardiogram (ECG) data, with a particular focus on improving the detection of minority arrhythmia classes.
In this study, the focus was on investigating the performance of three different supervised machine learning models in the context of arrhythmia detection. These models included Support Vector Machine (SVM), Logistic Regression (LR) and Random Forest (RF). An analysis was conducted using real inter-patient electrocardiogram (ECG) records, which is a more realistic scenario in a clinical environment where ECG data comes from various patients.
The study evaluated the models’ performances based on four important metrics: accuracy, precision, recall, and f1-score. After thorough experimentation, the results highlighted that the Random Forest (RF) classifier outperformed the other methods in all of the metrics used in the experiments. This classifier achieved an impressive accuracy of 0.94, indicating its effectiveness in accurately detecting arrhythmia in diverse ECG signals collected from different patients.
