Pradeep Singla

Follower

Following

Co-author

Public Views

Uploads

Papers by Pradeep Singla

An Optimized Design of Reversible Sequential Digital Circuits

arXiv (Cornell University), Jun 10, 2013

Download

Towards the Solution of Power Dissipation in Electronics Systems through Thermodynamics

arXiv (Cornell University), Apr 25, 2012

Power loss in the electronic system is a limiting fector that can be reduced or minim help of usi... more Power loss in the electronic system is a limiting fector that can be reduced or minim help of using the reversible logics " a conce Thermodynamics". In this paper the autho concept of reversible logics for the Electr The logical and physical designing approa the paper in detail. The contradiction o physical reversibility with the convent designing is also shows and the solu contradiction is also proposed by the a adiabatic logic. This Paper gives a compl idea if the thermodynamical concept for t industries for power reduction.

Download

Reversible Programmable Logic Array (RPLA) using Feynman & MUX Gates for Low Power Industrial Applications

arXiv (Cornell University), Apr 24, 2012

This paper present the research work directed towards the design of reversible programmable logic... more This paper present the research work directed towards the design of reversible programmable logic array using very high speed integrated circuit hardware description language (VHDL). Reversible logic circuits have significant importance in bioinformatics, optical information processing, CMOS design etc. In this paper the authors propose the design of new RPLA using Feynman & MUX gate. VHDL based codes of reversible gates with simulating results are shown .This proposed RPLA may be further used to design any reversible logic function or Boolean function (Adder, Subtractor etc.) which dissipate very low or ideally no heat.

Download

An Improved Structure Of Reversible Adder And Subtractor

arXiv (Cornell University), Jun 8, 2013

In today's world everyday a new technology which is faster, smaller and more complex than its pre... more In today's world everyday a new technology which is faster, smaller and more complex than its predecessor is being developed. The increased number of transistors packed onto a chip of a conventional system results in increased power consumption that is why Reversible logic has drawn attention of Researchers due to its less heat dissipating characteristics. Reversible logic can be imposed over applications such as quantum computing, optical computing, quantum dot cellular automata, low power VLSI circuits, DNA computing. This paper presents the reversible combinational circuit of adder, subtractor and parity preserving subtractor. The suggested circuit in this paper are designed using Feynman, Double Feynman and MUX gates which are better than the existing one in literature in terms of Quantum cost, Garbage output and Total logical calculations.

Download

Power Gating Structure for Reversible Programmable Logic Array

Zenodo (CERN European Organization for Nuclear Research), Sep 25, 2015

Throughout the world, the numbers of researchers or hardware designer struggle for the reducing o... more Throughout the world, the numbers of researchers or hardware designer struggle for the reducing of power dissipation in low power VLSI systems. This paper presented an idea of using the power gating structure for reducing the sub threshold leakage in the reversible system. This concept presented in the paper is entirely new and presented in the literature of reversible logics. By using the reversible logics for the digital systems, the energy can be saved up to the gate level implementation. But at the physical level designing of the reversible logics by the modern CMOS technology the heat or energy is dissipated due the sub-threshold leakage at the time of inactivity or standby mode. The Reversible Programming logic array (RPLA) is one of the important parts of the low power industrial applications and in this paper the physical design of the RPLA is presented by using the sleep transistor and the results is shown with the help of TINA-PRO software. The results for the proposed design is also compare with the CMOS design and shown that of 40.8% of energy saving. The Transient response is also produces in the paper for the switching activity and showing that the proposed design is much better that the modern CMOS design of the RPLA.

Download

A New Approach of Improving CFA Image for Digital Camera's

arXiv (Cornell University), Apr 24, 2012

This paper work directly towards the improving the quality of the image for the digital cameras a... more This paper work directly towards the improving the quality of the image for the digital cameras and other visual capturing products. In this Paper, the authors clearly defines the problems occurs in the CFA image. A different methodology for removing the noise is discuses in the paper for color correction and color balancing of the image. At the same time, the authors also proposed a new methodology of providing denoisiing process before the demosaickingfor the improving the image quality of CFA which is much efficient then the other previous defined. The demosaicking process for producing the colors in the image in a best way is also discuss.

Download

Reversible Squaring Circuit for Low Power Digital Signal Processing

Journal of Engineering Science and Technology Review, 2014

Power Gating Structure for Reversible Programmable Logic Array

Electrical & Computer Engineering: An International Journal, 2015

Download

Towards the Solution of Power Dissipation in Electronics Systems through Thermodynamics

Download

An Optimized Design of Reversible Sequential Digital Circuits

In the today's era, reversible logics are the promising technology for the designing of low p... more In the today's era, reversible logics are the promising technology for the designing of low power digital logic system having major application in the field of nanotechnology, quantum computation, DNA and other low power digital circuits. Reversible logics provide zero power dissipation (Ideally) in the digital operations. There are numbers of circuit designed by the reversible logics and sequential circuits have their own importance in the digital systems. In this paper authors provides a optimized approach and optimized design for the sequential circuit (counter as an example) by using the MUX gate (a reversible gate) which provides the better results against the previous designs discussed in the literature. The proposed design has lower quantum cost, garbage output, constant input and total number of logical calculations performing by the design.

DSTN (Distributed Sleep Transistor Network) for Low Power Programmable Logic array Design

With the high demand of the portable electronic products, Low- power design of VLSI circuits & Po... more With the high demand of the portable electronic products, Low- power design of VLSI circuits & Power dissipation has been recognized as a challenging technology in the recent years. PLA (Programming logic array) is one of the important off shelf part in the industrial application. This paper describes the new design of PLA using power gating structure sleep transistor at circuit level implementation for the low power applications. The important part of the power gating design i.e. header and footer switch selection is also describes in the paper. The simulating results of the proposed architecture of the new PLA is shown and compared with the conventional PLA. This paper clearly shows the optimization in the reduction of power dissipation in the new design implementation of the PLA. The transient response of the power gates structure of PLA is also illustrate in the paper by using TINA-PRO software.

A Cost- Effective Design of Reversible Programmable Logic Array

International Journal of Computer Applications, 2012

Promoting Short Term Load Forecasting by Using Artificial Intelligence

Load forecasting has always been the essential part of an efficient power system planning and ope... more Load forecasting has always been the essential part of an efficient power system planning and operation. Several electric power companies are now forecasting power demand (load) based on conventional methods and some on the behalf of artificial intelligence. On the behalf of that review, this paper presents the short term load forecasting on the basis of MAPE and MAE accuracy criteria by using time series as an input pattern selection for neural networks. The input data is trained by FFNN and in an another model to overcome the drawback of Gradient descent algorithm problem of local minima another global search algorithms GA is used for initialization of input parameters of neural network called GANN technique. The data used for the analysis is collected for the year 2012 from Ontario Electricity Market and prediction is done on time series frame work for first four weeks of December 2012. Key WordsElectricity Market, Load Forecasting, Neural

Solar Irradiation Forecasting by Long-Short Term Memory Using Different Training Algorithms

Studies in Infrastructure and Control, Sep 29, 2021

Deep learning nowadays is the hottest research topic with wide applications in various areas clas... more Deep learning nowadays is the hottest research topic with wide applications in various areas classifications, pattern recognition, solar forecasting, wind forecasting, etc. This paper presents the forecasting of one step ahead solar global horizontal irradiance (GHI) by long-short term memory (LSTM) deep learning network using three different training algorithms. The LSTM network is employed using three different training algorithms: adaptive moment estimation with momentum (ADAM), stochastic gradient descent with momentum (SGDM), and root mean square propagation (RMSprop). The 1 year of dataset is used for the training of the model, whereas monthly data is used to test the model. The two popular error metrics: root mean square error (RMSE) and mean absolute percentage error (MAPE) is considered to obtain the forecasting errors for each training algorithms-based LSTM model. The results prove that the LSTM with ADAM training algorithm outperforms the SGDM and RMSprop algorithm. The ADAM-based LSTM obtained the annual average RMSE of 68.62 (w/m2) and MAPE of 10.30%.

A dual decomposition with error correction strategy based improved hybrid deep learning model to forecast solar irradiance

Energy Sources, Part A: Recovery, Utilization, And Environmental Effects, Mar 25, 2022

ABSTRACT An accurate forecasting of solar irradiation plays a vital role in grid balancing, sched... more ABSTRACT An accurate forecasting of solar irradiation plays a vital role in grid balancing, scheduling, and maintenance. With this aim, a deep learning solar forecasting model based on dual decomposition with error correction strategy is proposed in this paper. In this model, historical time series of solar irradiance and error series are decomposed using complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and variational mode decomposition (VMD), respectively. The bidirectional long short-term memory (BiLSTM) deep learning (DL) network is used with each series to extract the different long- and short-term characteristics of the data. To observe the forecasting accuracy of the proposed model, nine contrast models are built to estimate one to three steps ahead solar irradiance for two different locations. The experimental results demonstrate that the proposed model achieved lower RMSE (1.81 W/m2–28.46 W/m2) and MAPE (0.2–4.40%) compared to the considered models. It improves the RMSE (17.55–72.82%) and MAPE (2.65–74.66%) over a non-error correction strategy-based hybrid model. In addition, the improvement in RMSE (13.82–65.10%) and MAPE (11.46–68.33%) are observed over single decomposition-based error correction model. Moreover, to validate the forecasting performance of the proposed model Diebold–Mariano Hypothesis (DMH) test, percentage improvement and its behavior in different weather conditions are also presented.

A Hybrid Solar Irradiance Forecasting Using Full Wavelet Packet Decomposition and Bi-Directional Long Short-Term Memory (BiLSTM)

Arabian journal for science and engineering, Mar 11, 2022

An ensemble method to forecast 24-h ahead solar irradiance using wavelet decomposition and BiLSTM deep learning network

Earth Science Informatics, Nov 17, 2021

In recent years, the penetration of solar power at residential and utility levels has progressed ... more In recent years, the penetration of solar power at residential and utility levels has progressed exponentially. However, due to its stochastic nature, the prediction of solar global horizontal irradiance (GHI) with higher accuracy is a challenging task; but, vital for grid management: planning, scheduling & balancing. Therefore, this paper proposes an ensemble model using the extended scope of wavelet transform (WT) and bidirectional long short term memory (BiLSTM) deep learning network to forecast 24-h ahead solar GHI. The WT decomposes the input time series data into different finite intrinsic model functions (IMF) to extract the statistical features of input time series. Further, the study reduces the number of IMF series by combining the wavelet decomposed components (D1-D6) series on the basis of comprehensive experimental analysis with an aim to improve the forecasting accuracy. Next, the trained standalone BiLSTM networks are allocated to each IMF subseries to execute the forecasting. Finally, the forecasted values of each sub-series from BiLSTM networks are reconstructed to deliver the final solar GHI forecast. The study performed monthly solar GHI forecasting for one year dataset using one month moving window mechanism for the location of Ahmedabad, Gujarat, India. For the performance comparison, the naïve predictor as a benchmark model, standalone long short term memory (LSTM), gated recurrent unit (GRU), BiLSTM and two other wavelet-based BiLSTM models are also simulated. From the results, it is observed that the proposed model outperforms other models in terms of root mean square error (RMSE) & mean absolute percentage error (MAPE), coefficient of determination (R 2) and forecast skill (FS). The proposed model reduces the monthly average RMSE by range from 26.04-58.

Download

A New Approach of Improving CFA Image for Digital Camera's

arXiv (Cornell University), Apr 24, 2012

Download

One Hour Ahead Solar Irradiation Forecast by Deep Learning Network Using Meteorological Variables

Springer eBooks, 2022

Review of Different Error Metrics: A Case of Solar Forecasting

The AIUB journal of science and engineering, Dec 30, 2021

Renewable energy systems (RES) are no longer confined to being used as a stand-alone entity in th... more Renewable energy systems (RES) are no longer confined to being used as a stand-alone entity in the modern era. These RES, especially solar panels are also used with the grid power systems to supply electricity. However, precise forecasting of solar irradiance is necessary to ensure that the grid operates in a balanced and planned manner. Various solar forecasting models (SFM) are presented in the literature to produce an accurate solar forecast. Nevertheless, each model has gone through the step of evaluation of its accuracy using some error measures. Many error measures are discussed in the literature for deterministic as well as probabilistic solar forecasting. But each study has its own selected error measure which sometimes landed on a wrong interpretation of results if not selected appropriately. As a result, this paper offers a critical assessment of several common error metrics with the goal of discussing alternative error metrics and establishing a viable set of error metrics for deterministic and probabilistic solar forecasting. Based on highly cited research from the last three years (2021-2019), error measures for both types of forecasting are presented with their basic functionalities, advantages & limitations which equipped the reader to pick the required compatible metrics Index Terms-Error measures, deterministic forecasting, probabilistic forecasting, solar forecasting, root mean square error.

Download

An Optimized Design of Reversible Sequential Digital Circuits

arXiv (Cornell University), Jun 10, 2013

Download

Towards the Solution of Power Dissipation in Electronics Systems through Thermodynamics

arXiv (Cornell University), Apr 25, 2012

Download

Reversible Programmable Logic Array (RPLA) using Feynman & MUX Gates for Low Power Industrial Applications

arXiv (Cornell University), Apr 24, 2012

Download

An Improved Structure Of Reversible Adder And Subtractor

arXiv (Cornell University), Jun 8, 2013