nonlinear neural network system
AN EFFICIENT SUPER PEER SELECTION ALGORITHM FOR PEER TO PEER (P2P) LIVE STREAMING NETWORK
... using nonlinear neuron identification models namely NARX and ...the nonlinear system identification model undergoing for vortex induced vibration of marine riser depends on Neural ...
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Identification and Adaptive Control of Dynamic Nonlinear Systems Using Sigmoid Diagonal Recurrent Neural Network
... the neural network controller output to get the appropriate values that can efficiently reduce the MSE between the actual reference t model and the nonlinear system output ...
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Complex Nonlinear System Modelling and Parameters Identification by Deep Neural Networks
... inherently nonlinear in nature, many efforts have been made to improve the understanding of complicated nonlinear ...identify nonlinear systems by conventional methods such as machine ...complex ...
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Two degree of freedom Robust Control for a Non minimum Phase Electro hydraulic System
... The increasing numbers of works dealing with EHA system over the past decades involved a linear control, intelligent contol and nonlinear control approaches such as neural network NN [0][r] ...
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Adaptive Neural Network Tracking Control for a Class of SISO Affine Nonlinear Uncertain Systems
... the system (1).Suppose that Assumption1-3 are satisfied and the neural network approximation error in (14) is bounded , then the neural network controller and adaptation law given by ...
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Dynamical Nonlinear Neural Networks with Perturbations Modeling and Global Robust Stability Analysis
... for absolute stability for HNN is presented. In particular, it has focused on networks with perturbations. A proper Lyapunov function is constructed and employed to present a sufficient condition for the asymptotic and ...
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INTELLIGENT SELF TUNING PID CONTROLLER USING HYBRID IMPROVED PARTICLE SWARM OPTIMIZATION FOR ULTRASONIC MOTOR
... on system identification models under vortex induced vibration (VIV) has been verified in this ...Two System identification methods used to create models which are: Neural Network based on ...
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Design of radial basis function neural network controller for BLDC motor control system
... Neural network as an intelligent control algorithm, is known for its strong capacities of self-learning, self-adapting and self-organization, and it is suitable for the control of nonlinear ...(RBF) ...
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Duct Modeling Using the Generalized RBF Neural Network for Active Cancellation of Variable Frequency Narrow Band Noise
... RBF neural network (DM RBF), which has the capability of modeling the nonlinear behavior, can suppress a variable-frequency narrow band noise of a duct more efficiently than an FX-LMS ...RBF ...
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Dynamic Threshold Selection for Sequential Learning in Radial Basis Function Networks
... for nonlinear system identification have evolved over the years to provide better and faster learning capabilities with increasing automation of ...the network. Automation as such allows ...
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Nonlinear System Identification Using Hammerstein-Wiener Neural Network and subspace algorithms
... on nonlinear system identification which use block-oriented ...forward neural network to model the static nonlinear[13], least square and SVD for Hammerstein model[11],[8], recursive ...
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Modeling and simulation in water turbine generator set systems
... control System has the characteristics of nonlinear, time varying, unsteady, so traditional PID has low control ...CMAC neural network can adjust dynamically by algorithm learning has the ...
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ABSTRACT: Chaos and chaos control are new theories and new fields of nonlinear dynamics. Chaotic motion
... Artificial neural network has been proved to have the characteristics of arbitrary approximation to nonlinear ...artificial neural network with chaotic system, some scholars have ...
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Development of a new EDRNN procedure in control of human arm trajectories
... of neural network mapping, evolutionary computation, and dynamic system ...control system structure is proposed to manipulate the complicated nonlinear dynamical arm ...recurrent ...
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Research of adaptive control algorithm research based on rough set and implementation
... adaptive neural network algorithm has strong compatibility, some noise data, not including related function and reduce the input dimension, a fast learning process, uncertainty processing and force ...
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A Machine Learning Approach for Secure Intrusion Detection in Wireless Sensor Networks
... wireless network traffic information in node or system frameworks and deploys different methods to give security ...permits network administrators to distinguish security target ...to network ...
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Gyroscope Random Drift Modeling, using Neural Networks, Fuzzy Neural and Traditional Time- series Methods
... suspension system, the dynamically induced 1negative2 spring rate cancels the spring rate of the ;exure suspensionC and makes the gyro free for small angles of ...
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Artificial Neural Network Classification for Gunshot Detection and Localization System
... As shown in Figure 5, the classified gunshot passed through the two filters implemented in the system. A band- pass filter was designed to remove unwanted signals. After the filtering process, the time of arrival ...
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The modified probabilistic neural network as a nonlinear correlator detector
... A neural network can be developed to embody this model and provide a continuous nonlinear correlator output r(x) as the vector x is taken from the process signal by sliding [r] ...
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Comparison of Fuzzy Logic & Hybrid Controller based DTC Technique of Induction Motor
... Ubaidullah Received B.Tech. degree from Sagar Institutue of Technology and Management, Barabanki, Uttar Pradesh (Dr. A.P.J. Abdul Kalam Technical University, formerly known as UPTU) in Electrical Engineering in 2014 and ...
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