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IEEE International Conference on Signal Processing, Computing and Control (ISPCC)

作者： Parul Puri Parul Garg Mona Aggarwal Division of Electronics and Communication Engineering Netaji Subhas Institute of Technology New Delhi India

ISBN: (纸本)9781479984374

This paper presents a relay selection scheme for a multiple relayed free-space optical (FSO) communication network. The considered FSO network consists of two non line-of-sight terminal nodes and multiple two-way relays (TWR). In order to establish a communication link between the terminal nodes, two TWRs are selected using partial relay selection protocols. The partial relay selection protocols reduce the channel state information requirements of the system. Further, by using two relays, the advantages of cooperative diversity are achieved. The system performance is evaluated in terms of outage probability, considering an optical channel that is affected by atmospheric turbulence induced fading and pointing errors. Further, the numerical results demonstrate that system performance can be significantly improved by using the proposed relay selection scheme.

关键词： Yttrium Signal to noise ratio

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Design and analysis of improved fractional order Butterworth lowpass filters

Design and analysis of improved fractional order Butterworth...

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IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)

作者： Dharmendra K. Upadhyay Tanya Khanna Division of Electronics & Communication Engineering Netaji Subhas Institute of Technology New Delhi India

In this paper, the genetic algorithm is used to improve the performance of fractional order lowpass filters with Butterworth approximation. This improvement is obtained by using the coefficient optimization and suitable scaling to approximate the ideal frequency response. Further, the error analysis of the designed and the existing filters with the performance of ideal ones is given to see the effectiveness of this optimization technique in the improvement of performance of designed filters over the existing filters in both, the passband and the stopband.

关键词： Filtering algorithms Passband Filtering theory Genetic algorithms Frequency response Optimization Transfer functions

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Half-integrator approximation analysis and its realizations

Half-integrator approximation analysis and its realizations

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International Conference on Soft Computing Techniques and Implementations (ICSCTI)

作者： P. Varshney Division of Instrumentation and Control Engineering Netaji Subhas Institute of Technology Dwarka New Delhi INDIA

Due to the absence of appropriate mathematical methods, fractional order dynamic systems were studied only marginally in both theory and practice. In this paper, continuous-time and discrete-time approximations of half integrator have been analyzed and compared. An approach for the realization of half integrator is also presented. MATLAB simulation results are presented and comparisons performed with the ideal continuous-time domain half integrator. Analog Realizations of some of the s-domain models has also been discussed. Discrete Realizations of the z-domain models have been developed and results compared with the ideal continuous-time domain models.

关键词： Read only memory

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Application of Probabilistic Neural Network in Fault Diagnosis of Wind Turbine Using FAST, TurbSim and Simulink

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Procedia computer Science 2015年 58卷 186-193页

作者： Hasmat Malik Sukumar Mishra Department of Electrical Engineering Indian Institute of Technology Delhi New Delhi-110016 India ICE Division Netaji Subhas Institute of Technology New Delhi-110078 India

This paper presents an intelligent diagnosis technique for wind turbine imbalance fault identification based on generator current signals. For this aim, Probabilistic Neural Network (PNN), which is powerful algorithm for classification problems that needs small training time in solving nonlinear problems and applicable to high dimension applications, is employed. The complete dynamics of a permanent magnet synchronous generator (PMSG) based wind-turbine (WTG) model are imitated in an amalgamated domain of Simulink, FAST and TurbSim under six distinct conditions, i.e., aerodynamic asymmetry, rotor furl imbalance, tail furl imbalance, blade imbalance, nacelle-yaw imbalance and normal operating scenarios. The simulation results in time domain of the PMSG stator current are decomposed into the Intrinsic Mode Frequency (IMF) using EMD method, which are utilized as input variable in PNN. The analyzed results proclaim the effectiveness of the proposed approach to identify the healthy condition from imbalance faults in WTG. The presented work renders initial results that are helpful for online condition monitoring and health assessment of WTG.

关键词： TurbSim FAST Simulink EMD ANN Wind Turbine Fault Diagnosis Condition Monitoring Imbalance Faults Current Signals

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Efficient air pollutants prediction using ANFIS trained by Modified PSO algorithm

Efficient air pollutants prediction using ANFIS trained by M...

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International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions)

作者： S. Sharma U. Kalra S. Srivathsan K.P.S. Rana V. Kumar Instrumentation and Control Engineering Division Netaji Subhas Institute of Technology Dwarka New Delhi India

In the modern day world air pollution has been a major concern for various environmental diseases. High traffic density, electricity production, and expanding commercial and industrial activities have increased air pollution in an unpredictable manner. Thus, the forecast of air pollution can be used as an advisory to establish strategies and corrective measures particularly in case of higher air pollution levels. In view of this, in this work we investigate an application of Modified Particle Swarm Optimization (MPSO) to train ANFIS (Adaptive Neuro Fuzzy Inference System) for the efficient prediction of two major air pollutants namely, Sulphur dioxide (SO 2 ) and Ozone (O 3 ) in New Delhi. The results obtained are then compared with the traditional gradient based method normally used for training ANFIS. The comparison between the two was based on three performance indices, namely MSE (Mean Squared Error), RMSE (Root Mean Squared Error) and MAD (Mean Absolute Deviation). For SO 2 prediction MSE, RMSE and MAD of 0.110, 0.331 and 0.932 were obtained using the proposed method against 0.117, 0.342 and 1.03 respectively using the traditional method. Similarly for O 3 prediction, MSE, RMSE and MAD of 0.837, 0.700 and 2.49 were obtained against 0.878, 0.812 and 2.93 respectively. These results clearly indicate that ANFIS trained using MPSO is far better at generalizing, achieving higher accuracy for the prediction of SO 2 and O 3 air pollutants.

关键词： Air pollution Artificial neural networks Training Fuzzy logic Firing Atmospheric measurements Particle swarm optimization

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Performance analysis of a PLC system over log-normal fading channel and impulsive noise

Performance analysis of a PLC system over log-normal fading ...

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International Conference on Computing and Network Communications

作者： Manan Jani Parul Gargt Ankur Bansal Division of Electronics and Communication Engineering Netaji Subhas Institute of Technology Dwarka New Delhi-110078 India

ISBN: (纸本)9781467373104

In this paper, we present the performance analysis of a Power Line Communication (PLC) system over log-normal fading channel assuming binary phase shift keying modulation scheme. The channel is also corrupted by additive impulsive noise and background noise. We derive the probability density function ( p.d.f.) of the noise and using it, we find the closed form expressions for the bit error rate (BER) and outage probability. Finally, the numerical results are presented.

关键词： Power Line Communication Systems impulsive noise background noise log - normal fading

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An Approach for Object Picking using Correlation analysis and Robotic Manipulation

An Approach for Object Picking using Correlation analysis an...

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International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions)

作者： S. Pradeep Asha Rani Vijander Singh Shivangi Agarwal University of Delhi Delhi Instrumentation and Control Engineering Division Netaji Subhas Institute of Technology Dwarka New Delhi

The aim of the present work is to pick and place an object with the help of robotic manipulator using computer vision. Real time object detection is achieved using a camera to capture the image in the region of interest (ROI). 2-D correlation between the object and captured image, along with image processing techniques, locates the object position. The pixel coordinates are then converted to real time distance coordinates. The object location is conveyed to the robotic arm with the help of software instructions and required operation of pick/place is performed. The object is successfully located and grabbed by the robotic arm, provided the relative position of the robotic arm and the camera is fixed. The method uses two-dimensional image analysis in place of three-dimensional object detecting techniques. Hence the proposed algorithm is simple, requires less memory space, does not require any filter, reduces the instruction set and has high accuracy.

关键词： Robot kinematics Cameras Robot vision systems Correlation Object detection Manipulators

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Efficient multi-parametric uncertainty quantification methods for EMC/EMI applications

Efficient multi-parametric uncertainty quantification method...

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IEEE Symposium on Electromagnetic Compatibility and Signal Integrity

作者： Zixi Gu Xingqi Zhang Neeraj Sood Costas D. Sarris Division of Electronics and Communication Engineering Netaji Subhas Institute of Technology New Delhi India University of Toronto Toronto ON CA

ISBN: (纸本)9781479919949

For years, statistical uncertainty in high-frequency circuits had been analyzed by post-processing data from repetitive simulations. Not surprisingly, this approach is extremely time consuming and hardly within the time constraints of a typical engineering design cycle. Recently, several new computational algorithms have been presented, which offer a fresh perspective to this old problem. This paper emphasizes approaches that stem from the polynomial chaos expansion method along with promising hybrid methods that can lead to efficient multi-parametric uncertainty quantification solvers.

关键词： Algorithm design and analysis Monte Carlo methods Chaos Acceleration Erbium

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Meeting Our Obligations and Making a Difference [Editorial]

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IEEE Systems, Man, and Cybernetics Magazine 2016年第4期2卷 3-3页

作者： M.E. El-Hawary Azad Hind FaujMarg Sector- 3 Netaji Subhas Institute of Technology Dwarka New Delhi India UESTC School of Computer Science & Engineering Chengdu China

Presents the introductory editorial for this issue of the publication.

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Dual lexical chaining for context based text classification

Dual lexical chaining for context based text classification

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International Conference on Advances in computer engineering and Applications (ICACEA)

作者： S. Chakraverty B. Juneja U. Pandey A. Arora Department of Computer Engineering Netaji Subhas Institute of Technology Dwarka New Delhi INDIA Department of Computer Sciences & Engineering IMS Engineering College Ghaziabad UP INDIA

Text Classification enhances the accessibility and systematic organization of the vast reserves of data populatingthe world-wide-web. Despite great strides in the field, the domain of context driven text classification provides fresh opportunities to develop more efficient context oriented techniques with refined metrics. In this paper, we propose a novel approach to categorize text documents using a dual lexical chaining technique. The algorithm first prepares a cohesive category-keyword matrix by feeding category names into the WordNet and Wikipedia ontology, extracting lexically and semantically related keywords from them and then adding to the keywords by employing a keyword enrichment process. Next, the WordNet is referred again to find the degree of lexical cohesiveness between the tokens of a document. Terms that are strongly related are woven together into two separate lexical chains; one for their noun senses and another for their verb senses, that represent the feature set for the document. This segregation enables a better expression of word cohesiveness as concept terms and action terms are treated distinctively. We propose a new metric to calculate the strength of a lexical chain. It includes a statistical part given by Term Frequency-Inverse Document Frequency-Relative Category Frequency (TF-IDF-RCF) which itself is an improvement upon the conventional TF-IDF measure. The chain's contextual strength is determined by the degree of its lexical matching with the category-keyword matrix as well as by the relative positions of its constituent terms. Results indicate the efficacy of our approach. We obtained an average accuracy of 90% on 6 categories derived from the 20 News Group and the Reuters corpora. Lexical chaining has been applied successfully to text summarization. Our results indicate a positive direction towards its usefulness for text classification.

关键词： Training Encyclopedias computers Electronic publishing Internet Semantics

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