In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is applied to learn the control structure for self-tuning PID type neuro-controller. Where the neural network is used to minimize the error function by adjusting the PID gains. Simulation results show that the self-tuning PID scheme can deal with a large unknown nonlinearity
In this paper, the dynamical behavior of a three-dimensional fractional-order prey-predator model is investigated with Holling type III functional response and constant rate harvesting. It is assumed that the middle predator species consumes only the prey species, and the top predator species consumes only the middle predator species. We also prove the boundedness, the non-negativity, the uniqueness, and the existence of the solutions of the proposed model. Then, all possible equilibria are determined, and the dynamical behaviors of the proposed model around the equilibrium points are investigated. Finally, numerical simulations results are presented to confirm the theoretical results and to give a better understanding of the dynami
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In this note, we present a component-wise algorithm combining several recent ideas from signal processing for simultaneous piecewise constants trend, seasonality, outliers, and noise decomposition of dynamical time series. Our approach is entirely based on convex optimisation, and our decomposition is guaranteed to be a global optimiser. We demonstrate the efficiency of the approach via simulations results and real data analysis.
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Background: Spontaneous abortion means that a pregnancy is lost prior to viability, the loss of a fetus weighing less than 500 g, and the loss of an embryo or fetus at 20 weeks gestation or less (WHO, 2001). Glenville, (2001) has reported that suffering a miscarriage is one of the most devastating things that can happen to a woman, and to her husband. Many women conceive easily and are not emotionally or physically prepared for the shock of losing a baby. Objective: To know effects of spontaneous abortion upon physical status and spiritual beliefs , also find out the association between physical status and spi
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Cognitive-behavioral therapy is one of the most important relatively recent; treatment programs that attempt to modify behavior and control psychological disorders by modifying the individual's thinking style and awareness of himself and his environment, and cognitive reconstruction by replacing negative thoughts with positive ones. The current study aimed to know the effectiveness of a cognitive behavioral treatment program in reducing nervous fatigue among mothers of children with cerebral palsy. The sample on which the nervous fatigue scale was applied consisted of (30) mothers whose son suffers from cerebral palsy, and the results indicated that (24) mothers suffer from nervous fatigue. This sample was divided
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This paper describes a new proposed structure of the Proportional Integral Derivative (PID) controller based on modified Elman neural network for the DC-DC buck converter system which is used in battery operation of the portable devices. The Dolphin Echolocation Optimization (DEO) algorithm is considered as a perfect on-line tuning technique therefore, it was used for tuning and obtaining the parameters of the modified Elman neural-PID controller to avoid the local minimum problem during learning the proposed controller. Simulation results show that the best weight parameters of the proposed controller, which are taken from the DEO, lead to find the best action and unsaturated state that will stabilize the Buck converter system performan
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Objective : Multiple sclerosis (MS) is a common neurological disease deeply linked with the immune-inflammatory disorders whereas the term (multiple) mostly refers to the multi-focal zones of Inflammation caused by lymphocytes and macrophages infiltration besides oligodendrocytes death. Accordingly , the dysfunctional immune system able to damage myelin ( a pivotal component of the central nervous system ) which responsible for communication among neurons. The aim of the present study is to innovate a biochemical relationship between MS and thyroid hormones (THs) by highlighting immunological responses and also to examine the action of Interferon beta (IFNβ) drug on thyroid hormone (THs) and thyroid stimulation hormone (TSH). Materials and
... Show MoreFace Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a
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