This paper deals with the study of effect of fractional operators in chaotic systems. Chaos means randomness and irregularity. Some of the typical features of chaos are non-linearity, determinism, sensitivity to initi...
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Identification of optimal denoising algorithm for ECG signals using DWT is described. The parameters are determined by comparing different types of wavelet functions, decomposition levels and threshold selection metho...
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ISBN:
(纸本)9781424478835
Identification of optimal denoising algorithm for ECG signals using DWT is described. The parameters are determined by comparing different types of wavelet functions, decomposition levels and threshold selection methods. The algorithm is used to improve the SNR of the ECG contaminated by disturbances like power line interferences, to present a clean signal for accurate auto diagnosis.
This paper deals with the study of effect of fractional operators in chaotic systems. Chaos means randomness and irregularity. Some of the typical features of chaos are non-linearity, determinism, sensitivity to initi...
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This paper deals with the study of effect of fractional operators in chaotic systems. Chaos means randomness and irregularity. Some of the typical features of chaos are non-linearity, determinism, sensitivity to initial conditions and irregularity. In this paper, three s-to-z transformations viz. Tustin, Al-Alaoui and Maneesha-Pragya-Visweswaran operators have been used to obtain integer order approximations of fractional integrators in z-domain. The stability of the proposed models has been investigated. These discretizations can be applied for analysis of fractional order Chua systems. A comparison with the existing approximations is also presented. The major purpose of the paper is to emphasize that the z-domain approximations proposed in this paper can be used for hardware realizations.
An image consists of large data and requires more space in the memory. The large data results in more transmission time from transmitter to receiver. The time consumption can be reduced by using data compression techn...
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An image consists of large data and requires more space in the memory. The large data results in more transmission time from transmitter to receiver. The time consumption can be reduced by using data compression techniques. In this technique, it is possible to eliminate the redundant data contained in an image. The compressed image requires less memory space and less time to transmit in the form of information from transmitter to receiver. Artificial neural net- work with feed forward back propagation technique can be used for image compression. In this paper, the Bipolar Coding Technique is proposed and implemented for image compression and obtained the better results as compared to Principal Component Analysis (PCA) technique. However, the LM algorithm is also proposed and implemented which can acts as a powerful technique for image compression. It is observed that the Bipolar Coding and LM algorithm suits the best for image compression and processing applications.
An evocative solution for the brachistochrone problem is presented by Euler-Lagrange equation. The solution of brachistochrone problem by variational approach i.e. Euler-Lagrange equation leads to the curve of a cyclo...
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An evocative solution for the brachistochrone problem is presented by Euler-Lagrange equation. The solution of brachistochrone problem by variational approach i.e. Euler-Lagrange equation leads to the curve of a cycloid also known as brachistochrone curve. In this paper the exactness of the brachistochrone curve is verified through simulated studies in MATLAB, taking into cognizance different other curves viz. straight line and parabola along with cycloid. By computing the time taken by the bead in traversing the path between two points under gravity along all the curves considered, it is seen after comparison that the time taken along the cycloid is the least.
An artificial intelligence controller for three phase three level soft switched, phase shifted PWM(phase shift modulation) dc to dc converter is proposed for high voltage and high power applications. In which, it is a...
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The paper discusses about the application of PID controller and fuzzy controller in reactive distillation column. A generic mathematical model of reactive distillation has been taken for simulation. The PID and fuzzy ...
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The paper discusses about the application of PID controller and fuzzy controller in reactive distillation column. A generic mathematical model of reactive distillation has been taken for simulation. The PID and fuzzy controllers are designed for the process and then the overall process is controlled by using conventional (PID) and intelligent (fuzzy) controllers separately. Conventional PID controller is used to control the temperature of the column and then it is replaced by fuzzy controller and then the results from both the controllers are compared.
The rotor position is integrant information for vector control drive system of Permanent Magnet Synchronous Motor (PMSM). In this paper, the focus is on the rotor position of PMSM detecting by the resolver sensor. The...
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Identification of optimal denoising algorithm for ECG signals using DWT is described. The parameters are determined by comparing different types of wavelet functions, decomposition levels and threshold selection metho...
详细信息
Identification of optimal denoising algorithm for ECG signals using DWT is described. The parameters are determined by comparing different types of wavelet functions, decomposition levels and threshold selection methods. The algorithm is used to improve the SNR of the ECG contaminated by disturbances like power line interferences, to present a clean signal for accurate auto diagnosis.
Decentralized Partially Observable Markov Decision Processes (Dec-POMDPs) offer a powerful platform for optimizing sequential decision making in partially observable stochastic environments. However, finding optimal s...
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Decentralized Partially Observable Markov Decision Processes (Dec-POMDPs) offer a powerful platform for optimizing sequential decision making in partially observable stochastic environments. However, finding optimal solutions for Dec-POMDPs is known to be intractable, necessitating approximate/suboptimal approaches. To address this problem, this work proposes a novel fuzzy reinforcement learning (RL) based game theoretic controller for Dec-POMDPs. The proposed controller implements fuzzy RL on Dec-POMDPs, which are modeled as a sequence of Bayesian games (BG). The main contributions of the work are the introduction of a game based RL paradigm in a Dec-POMDP settings, and the use of fuzzy inference systems to effectively generalize the underlying belief space. We apply the proposed technique on two benchmark problems and compare results against state-of-the-art Dec POMDP control approach. The results validate the feasibility and effectiveness of using game theoretic RL based fuzzy control for addressing intractability of Dec-POMDPs, thus opening up a new research direction.
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