CHAOTIC NEURAL FUZZY ASSOCIATIVE MEMORY

1999 ◽  
Vol 09 (08) ◽  
pp. 1597-1617 ◽  
Author(s):  
HUBERT Y. CHAN ◽  
STANISLAW H. ŻAK
Keyword(s):  
Associative Memory ◽  
Memory Retrieval ◽  
Equilibrium Points ◽  
Activation Function ◽  
Brain State ◽  
Proposed Model ◽  
Fuzzy Associative Memory ◽  
Existence And Stability ◽  
Biological Neuron ◽  
Special Case

A chaotic neuron model with the linear saturating activation function is analyzed. The model accounts for the property of relative refractoriness, that is, gradual recovery of responsiveness of a biological neuron after a stimulus is applied to the neuron. A neural network model composed of chaotic neurons with the linear saturating activation functions, which includes the generalized Brain-State-in-a-Box (gBSB) model as a special case, is proposed and analyzed. The proposed model is then used to implement associative memory. The existence and stability of equilibrium points of the model are analyzed. Fuzzy logic is used to tune associative memory parameters for the purpose of directing the network trajectory to visit memory patterns with sought features. Simulation results are presented to illustrate the effectiveness of the memory retrieval capability.

On the Synthesis of Brain-State-in-a-Box Neural Models with Application to Associative Memory

2000 ◽  
Vol 12 (2) ◽  
pp. 451-472 ◽  
Author(s):  
Fation Sevrani ◽  
Kennichi Abe
Keyword(s):  
Neural Networks ◽  
Associative Memory ◽  
Equilibrium Points ◽  
Domain Of Attraction ◽  
Neural Model ◽  
Brain State ◽  
Qualitative Properties ◽  
The Stability ◽  
The Brain ◽  
Insight Into

In this article we present techniques for designing associative memories to be implemented by a class of synchronous discrete-time neural networks based on a generalization of the brain-state-in-a-box neural model. First, we address the local qualitative properties and global qualitative aspects of the class of neural networks considered. Our approach to the stability analysis of the equilibrium points of the network gives insight into the extent of the domain of attraction for the patterns to be stored as asymptotically stable equilibrium points and is useful in the analysis of the retrieval performance of the network and also for design purposes. By making use of the analysis results as constraints, the design for associative memory is performed by solving a constraint optimization problem whereby each of the stored patterns is guaranteed a substantial domain of attraction. The performance of the designed network is illustrated by means of three specific examples.

scholarly journals Theoretical Analysis of an Imprecise Prey-Predator Model with Harvesting and Optimal Control

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Anjana Das ◽  
M. Pal
Keyword(s):  
Complex Dynamics ◽  
Equilibrium Points ◽  
Uniform Boundedness ◽  
Optimal Harvesting ◽  
Model Parameters ◽  
Predator Species ◽  
Proposed Model ◽  
Existence And Stability ◽  
Predator Model ◽  
Predator System

In our present paper, we formulate and study a prey-predator system with imprecise values for the parameters. We also consider harvesting for both the prey and predator species. Then we describe the complex dynamics of the proposed model system including positivity and uniform boundedness of the system, and existence and stability criteria of various equilibrium points. Also the existence of bionomic equilibrium and optimal harvesting policy are thoroughly investigated. Some numerical simulations have been presented in support of theoretical works. Further the requirement of considering imprecise values for the set of model parameters is also highlighted.

scholarly journals A Study of Within-Host Dynamics of Dengue Infection incorporating both Humoral and Cellular Response with a Time Delay for Production of Antibodies

2021 ◽  
Vol 9 (1) ◽  
pp. 66-80
Author(s):  
Deva Siva Sai Murari Kanumoori ◽  
D Bhanu Prakash ◽  
D. K. K. Vamsi ◽  
Carani B Sanjeevi
Keyword(s):  
Immune Response ◽  
Sensitivity Analysis ◽  
Time Delay ◽  
Equilibrium Points ◽  
Dengue Infection ◽  
Complex Behaviour ◽  
Proposed Model ◽  
Existence And Stability ◽  
The Stability ◽  
Endemic State

Abstract a. Background: Dengue is an acute illness caused by a virus. The complex behaviour of the virus in human body can be captured using mathematical models. These models helps us to enhance our understanding on the dynamics of the virus. b. Objectives: We propose to study the dynamics of within-host epidemic model of dengue infection which incorporates both innate immune response and adaptive immune response (Cellular and Humoral). The proposed model also incorporates the time delay for production of antibodies from B cells. We propose to understand the dynamics of the this model using the dynamical systems approach by performing the stability and sensitivity analysis. c. Methods used: The basic reproduction number (R0) has been computed using the next generation matrix method. The standard stability analysis and sensitivity analysis were performed on the proposed model. d. Results: The critical level of the antibody recruitment rate(q) was found to be responsible for the existence and stability of various steady states. The stability of endemic state was found to be dependent on time delay(τ). The sensitivity analysis identified the production rate of antibodies (q) to be highly sensitive parameter. e. Conclusions: The existence and stability conditions for the equilibrium points have been obtained. The threshold value of time delay (τ0) has been computed which is critical for change in stability of the endemic state. Sensitivity analysis was performed to identify the crucial and sensitive parameters of the model.

scholarly journals Analysis of Smooth Implementation of Industry Poverty Alleviation considering Government Supervision

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Haifeng Yao ◽  
Jiangyue Fu
Keyword(s):  
Equilibrium Point ◽  
Evolutionary Game Theory ◽  
Poverty Alleviation ◽  
Equilibrium Points ◽  
Evolutionary Game ◽  
Parameter Design ◽  
Game Model ◽  
Government Supervision ◽  
Proposed Model ◽  
The Government

Vigorous implementation of industrial poverty alleviation is the fundamental path and core power of poverty alleviation in impoverished areas. Enterprises and poor farmers are the main participants in industry poverty alleviation. Government supervision measures regulate their behaviors. This study investigates how to smoothly implement industry poverty alleviation projects considering government supervision. A game model is proposed based on the evolutionary game theory. It analyses the game processes between enterprises and poor farmers with and without government supervision based on the proposed model. It is shown that poverty alleviation projects will fail without government supervision given that the equilibrium point (0, 0) is the ultimate convergent point of the system but will possibly succeed with government supervision since the equilibrium points (0, 0) and (1, 1) are the ultimate convergent point of the system, where equilibrium point (1, 1) is our desired results. Different supervision modes have different effects on the game process. This study considers three supervision modes, namely, only reward mode, only penalty mode, and reward and penalty mode, and investigates the parameter design for the reward and penalty mode. The obtained results are helpful for the government to develop appropriate policies for the smooth implementation of industry poverty alleviation projects.

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