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With the advancement in modulation schemes and cognitive techniques, Powerline Communications (PLC), have gained tremendous importance as a medium for transmission of variety of signals. The varied signals when sent through a common channel require a rigorous classification procedure for effective routing at both the transmission and receiving ends. In this paper we present complete software based,...
The paper presents an adaptive retraining procedure that starts from a previously trained artificial neural network (ANN). The system is retrained to learn the evolution of a non-stationary sequence, without forgetting completely the previously learned data. The optimal ANN architecture is selected and the set of delayed input vectors is replaced with their principal components. The method is used...
In order to improve the performance of switched reluctance driving system, it is necessary to build an accurate switched reluctance motor (SRM) model. In this paper, a nonlinear flux-linkage model and a torque model of SRM are presented by using the measured accurate flux-linkage data, torque data and nonlinear mapping ability of BP neural network, which is based on fast self-configuring algorithm...
Torque distribution based on the method of solving static model is not efficient in rough terrain. This paper describes an optimization method and neural network method based on the rover's static model. Through building the 3D virtual environment, simulation experiment supports the fact that both of them is better than solving static model method, and neural network method more timesaving than optimization...
The production period of the crystalline aluminium chloride is considerably long. However, the offline assay of AlCl3??6H2O content has large time delay. Thus soft sensor modeling is needed to analyze its content, and estimate the value to improve the product quality. The conventional back-propagation (BP) neural network training is easily trapped to the local minimum, To overcome this embarrassment,...
Providing a soft-sensing modeling method of vinyl acetate (VAC) polymerization rate based on BP neural network. Solving the current problem that the VAC polymerization rate in the polyvinyl alcohol (PVA) producing process is hard to real-time measuring. Using the data samples collected from the scene to train the network. In the network learning process, using the Levenberg-Marquardt optimization...
Stock price variation predictions are at the core of many research issues, and neural networks (NNs) are widely applied and were proven to be more efficient than time series forecasting for stock price forecasting. However, this type of research always determines the parameter settings of the NNs rationally through a trial-and-error methodology. This paper integrates design of experiment (DOE) and...
The main goal of this study was to develop a new method of estimating the angle of the passively stretched ankle joint, based on structural muscle spindle models of the tibial and peroneal electroneurograms (ENG). Passive ramp-and-hold and alternating stretches of the ankle joint were performed in a rabbit. Simultaneously, two cuff electrodes were used to record the ENGs of peroneal and tibial nerves...
The sensor node position estimation is essential in wireless sensor networks. Among many localization schemes, the position estimations based on Received Signal Strength Indicator (RSSI) are mostly used in various systems and applications. However, RSSI data are highly affected from multipath propagation caused by the reflections from walls or objects. These reasons conduct the improper phenomena...
We propose to use the Izhikevich single neuron model to represent a motor cortex neuron for studying a control-theoretic perspective of a neuroprosthetic system. The problem of estimating model parameters is addressed when the only available data from intracortical recordings of a neuron are the Inter-Spike Intervals (ISIs). Non-linear constrained and unconstrained optimization problems are formulated...
Wavelet neural network is a neural network combining the wavelet theory with neural network theory, which avoids nonlinear optimization problems such as blindness of the design of BP neural network structure and local optimum, greatly simplifying the training. The use of wavelet neural networks to forecast regional logistics demand provided an important reference for regional logistics systematic...
ANN has a wide application areas. One of these applications areas is the optimization of microwave filters. In this study, of optimization ANN solution techniques have been applied to optimize RF and microwave structures Using Artificial neural networks (ANN) modeling technique in a filter design with the inset-feeding open-loop resonator is presented. With helping the Sonnet EM Simulator, to develop...
The improved algorithm of WNN based on BP was proposed in this paper. Theoretical analysis and simulation result show it avoids both the blindness of framework designs for BP neural networks and the problem of nonlinear optimizations, such as local optimization. So it can simplify the training of neural networks. It has better abilities in function learning and generalization. This algorithm was successfully...
The instability disaster prediction model of tailings dam had been established, based on system analysis of the factors that caused the instability disaster of tailings dam, by selecting 6 prediction index, medium unit weight, cohesion, internal friction angle, slope angle, slope height and pore pressure ratio and combining with using theory of the rough set and neural network. First the rough set...
This article established artificial neural networks based on improved ant colony optimization evaluation model for residential performance. Firstly, on the basis of comprehensive analysis of the effects factors of residential building's performance, considering of the advantages of dealing with non-linear object of neural network, the neural network is trained by the sample data. While training neural...
This paper presents a novel technique for power quality disturbance classification. Wavelet transform (WT) has been used to extract some useful features of the power system disturbance signal and discrete harmony search with modified differential mutation operator (DHS_MD) have been used for feature dimension reduction in order to achieve high classification accuracy. Next, a probabilistic neural...
Powder Metallurgy (P/M) involves multiple input and output which are non-linearly related for which statistical optimization methods are not suitable. These considerations lead to adoption of neural network (NN) for proper selection of P/M process parameter. In the present work, white cast iron powder is taken as the work material and NN approach is employed which allows specification of multiple...
wireless capsule endoscopy (WCE) is an important device to detect abnormalities in small intestine. Despite emerging technologies, reviewing capsule endoscopic video is a labor intensive task and very time consuming. Computational tools which automatically detect informative frames and tag abnormal conditions such as bleeding, ulcer or tumor will dramatically reduce the clinician's effort. In this...
The following topics are dealt with: security of data; power line communication; radio networks; video streaming; telecommunication switching; optical communication; antenna; computer networks; modulation; diversity reception; mobile communication; optimization; artificial intelligence; neural nets; operations research; signal processing; medical computing; microprocessor chips; FPGA; power systems;...
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