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A new method for analyzing dynamics of continuous neural networks is proposed,and the necessary convergence conditions for a class of associative networks are obtained. Basedon the stability criterion and the equations of equilibrium set of the network, synthesis of aclass of associative neural networks is given. The stability control model of asymmetric unstablenetworks is suggested, which is also a valid way for optimization and dynamic control of stableneural networks. 相似文献
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In this paper the globally asymptotic stability of more general two-layer nonlinear feedback associative memory neural networks with time delays is examined. The sufficient conditions of existence, uniqueness and globally asymptotic stability of the equilibrum position are given. Finally, two interesting examples to illustrate the theory are given. 相似文献
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Testability analysis of neural architectures can be performed at a very high abstraction level on the computational paradigm. In this paper, we consider the case of feed-forward multi-layered neural networks. We introduce a behavioral error model which allows good mapping of the physical faults in widely different implementations. Conditions for error controllability, observability and global testability are analytically derived; their purpose is that of verifying whether it is possible to excite all modeled errors and to propagate the error's effects to the primary outputs (actual test vectors being then technological-dependent). Mapping of physical faults onto behavioral errors is performed for some representative, architectures. 相似文献
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刘小河 《电子科学学刊(英文版)》1995,12(4):312-318
The dynamic properties of continuous asymmetric neural networks are discussed in this paper. The condition in the existence of unique equilibrium point is obtained. It is also dealt with the conditions in not producing static bifurcation and Hopf's bifurcation and is put forward the sufficient conditions for overall asymptotic stability and exponential stability. 相似文献
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A reconfigurable low-voltage low-power cell that can function either as a synapse or a neuron is proposed and analyzed in this article for the VLSI implementation of artificial neural networks (ANNs). The measured results are also presented. The design is based on the current-mode approach and uses the square-law characteristics of an MOS transistor working in saturation. The proposed fabricated synapse/neuron cell utilizes I–V converters, current mirror, and a ±1 V power supply to achieve superior performance. Modularity, ease of interconnectivity, expandability and reconfigurability are the main advantages of this cell. 相似文献
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In this paper, the global exponential stability of an equilibrium position for general bidirectional associative memory neural networks are studied. The sufficient conditions of existence and uniqueness of the equilibrium position are given. The method of energy function is examined. Two examples are given to illustrate the theory. 相似文献
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Cellular Neural Networks (CNN) with feedback mode and M×N cells are equivalent to a network which possesses 2M×N cells, a neighborhood with mirror-like structure, space-variant templates and without feedback as well as without input templates. The stability of the CNN with feedback mode and transformations with the neighborhood of mirror-like structure are discussed. 相似文献
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Guo Baolong 《电子科学学刊(英文版)》1997,14(2):117-124
By comparison with constraint satisfaction networks, this paper presents an essential frame of the logical theory for continuous-state neural networks, and gives the quantitative analyzing method for contradiction. The analysis indicates that the basic reason for the alternation of the logical states of the neurons is the existence of superior contradiction inside the networks. The dynamic process for a neural network to find a solution corresponds to eliminating the superior contradiction. 相似文献
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Feng Dazheng Bao Zheng Jiao Licheng 《电子科学学刊(英文版)》1997,14(2):186-190
Novel distributed parameter neural networks are proposed for solving partial differential equations, and their dynamic performances are studied in Hilbert space. The locally connected neural networks are obtained by separating distributed parameter neural networks. Two simulations are also given. Both theoretical and computed results illustrate that the distributed parameter neural networks are effective and efficient for solving partial differential equation problems. 相似文献
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针对车辆路径的优化问题,借鉴旅行商路径问题的解决,利用Hopfield神经网络,结合电子地图和交通路况的一些人为因素(禁行、单行道等),提出了车辆行驶接近最优路径的算法和参数的学习方法。 相似文献
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On the predictability of next generation mobile network traffic using artificial neural networks
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I. Loumiotis E. Adamopoulou K. Demestichas T. Stamatiadi M. Theologou 《International Journal of Communication Systems》2015,28(8):1484-1492
Though the introduction of the new 4th Generation mobile access technologies promises to satisfy the increasing bandwidth demand of the end‐users, it poses in parallel the need for novel resource management approaches at the side of the base station. To this end, schemes that try to predict the forthcoming bandwidth demand using supervised learning methods have been proposed in the literature. However, there are still open issues concerning the training phase of such methods. In the current work, the authors propose a novel scheme that dynamically selects a proper training set for artificial neural network prediction models, based on the statistical characteristics of the collected data. It is demonstrated that an initial statistical processing of the collected data and the subsequent selection of the training set can efficiently improve the performance of the prediction model. Finally, the proposed scheme is validated using network traffic collected by real, fully operational base stations. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
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Surface Electromyography (sEMG) plays a key role in many applications such as control of Human-Machine Interfaces (HMI) and neuromusculoskeletal modeling. It has strongly nonlinear relations to joint kinematics and reflects the subjects’ intention in moving their limbs. Such relations have been traditionally examined by either integrated biomechanics and multi-body dynamics or gesture-based classification approaches. However, these methods have drawbacks that limit their usability. Different from them, joint kinematics can be continuously reconstructed from sEMG via estimation approaches, for instance, the Artificial Neural Networks (ANNs). The Comparison of different ANNs used in different studies is difficult, and in many cases, impossible. The current study focuses on fairly evaluating four types of ANN over the same dataset and conditions in proportional and simultaneous estimation of 15 hand joint angles from 10 sEMG signals. The presented ANNs are Feedforward, Cascade-Forward, Radial Basis Function (RBFNN), and Generalized Regression (GRNN). Each ANN is applied to its special parametric study. All the methods efficiently solved the regression problem of the complex multi-input multi-output bio-system. The RBFNN has the best performance over the others with a 79.80% mean correlation coefficient over all joints, and its accuracy reaches as high as 92.67% in some joints. Interestingly, the highest accuracy over individual joints is 93.46%, which is achieved via the GRNN. The good accuracy suggests that the proposed approaches can be used as alternatives to the previously adopted ones and can be employed effectively to synchronously control multi-degrees of freedom HMI and for general multi-joint kinematics estimation purposes. 相似文献
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Sanjeev Kulshrestha Deven J. Chheda S.B. Chakrabarty Rajeev Jyoti S.B. Sharma 《International Journal of Electronics》2013,100(12):1711-1720
This article presents the use of artificial neural networks for the evaluation of integrals with finite number of pole singularities while formulating the integral equation for the electric surface current density. A feed-forward single-layer back-propagated artificial neural network (ANN) model has been trained to approximate the discontinuous integrand function. Generation of a soft continuous function obtained from the ANN model and closed-loop expressions for the evaluation of the integrals are presented. The proposed technique is applied to compute the input impedance of microstrip antenna and results have been compared with IE3D. Integration has been performed using n-point Gaussian quadrature rule for evaluating the reaction matrix. 相似文献
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Zlatica Marinkovi? Giovanni CrupiDominique M.M.-P. Schreurs Alina CaddemiVera Markovi? 《Microelectronic Engineering》2011,88(10):3158-3163
Nowadays, FinFET represents a new and promising transistor structure for the aggressive downscaling of the CMOS technology. Typically, the small-signal modeling for FinFET is based on compact models or on equivalent circuit representations. As an alternative to such approaches, a small-signal behavioral model based on artificial neural networks is developed in this paper. Particular attention is devoted to modeling the low-frequency kinks of the scattering parameters, due to the lossy silicon substrate. The model is efficient and accurate, as confirmed by the comparison between measured and simulated microwave behavior. 相似文献
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We propose a novel mobility model, named Semi-Markov Smooth (SMS) model, to characterize the smooth movement of mobile users in accordance with the physical law of motion in order to
eliminate sharp turns, abrupt speed change and sudden stops exhibited by existing models. We formulate the smooth mobility
model by a semi-Markov process to analyze the steady state properties of this model because the transition time between consecutive
phases (states) has a discrete uniform distribution, instead of an exponential distribution. Through stochastic analysis,
we prove that this model unifies many good features for analysis and simulations of mobile networks. First, it is smooth and steady because there is no speed
decay problem for arbitrary starting speed, while maintaining uniform spatial node distribution regardless of node placement.
Second, it can be easily and flexibly applied for simulating node mobility in wireless networks. It can also adapt to different
network environments such as group mobility and geographic constraints. To demonstrate the impact of this model, we evaluate
the effect of this model on distribution of relative speed, link lifetime between neighboring nodes, and average node degree
by ns-2 simulations.
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Wenye WangEmail: |
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