hnn

Research on Evaluation Method of Human-Machine Interface of Power Plant Based on HNN

基于神经网络的火电厂人机界面评价方法研究

The HNN model considered the time delay of signal diffusion and had asymmetric weights .

HNN的连接权是非对称的，并且考虑了信号传播时延。

An interactive human-machine evaluation platform was designed using RBF neural network functions of the MATLAB HNN toolbox .

利用MATLAB神经网络工具箱中的RBF神经网络函数设计出人机交互的人机界面评价平台。

Third , HNN method is sensitive to the topology of the problem but SOFM does not .

SOFM算法对待解决问题的拓扑分布不敏感，而HNN算法的收敛性对待求解问题的自身分布有很强的依赖性；

Based on the principle of HNN optimization computation , a design method for the observer for linear time invariant systems is proposed .

基于神经优化计算原理，给出了线性定常系统的状态观测器的设计方法。

In this paper , we analyzed the speciality of GA and HNN , and gave an accelerating method .

文章简要分析了GA和HNN算法的特点，并将两种算法有机地相结合，提出了一种加速方法。

This paper analyzes immune theory and Hopfield Neural Network ( HNN ), and then proposes a new algorithm for multimodal function .

本文分析了免疫算法和Hopfield神经网络的优缺点，提出了一种解决多峰值函数优化问题的混合算法。

A new image reconstruction algorithm of computer tomography from fewer views based on the continuous Hopfield neural network ( HNN ) is presented .

基于连续型Hopfield神经网络（HNN）提出了一种新的少数投影CT图像重建算法。

The parallel stability of HNN

HNN的并行稳定性

In this paper a novel parameter identification method for linear system is developed based on the optimization computing theory of Hopfield Neural Networks ( HNN ) .

基于Hopfield神经网络的优化计算原理，提出了一种新的线性系统参数辨识方法。

Second , HNN method depends on parameters and initial state strongly , but setting and adjusting parameters are quite easy in SOFM algorithm .

HNN对网络模型参数和初始条件具有很强的依赖性且调整参数组合非常困难，而SOFM的参数设置和调整相对要简单得多；

The Lagrange object relaxation technique can help the HNN escape from the local minimum by correcting Lagrange multipliers .

拉格朗日对象松弛技术能够通过调节拉格朗日因子帮助HNN脱离目前的局部极小值。

Numerical simulation shows that TCNN has higher ability of searching for globally optimal to TSP problem than HNN and higher efficiency of searching .

仿真结果表明，TCNN比HNN具有更强的全局寻优能力和更高的搜索效率。

Combining augmented lagrange multiplier ( ALM ) method to Hopfield neural network ( HNN ), was proposed to solve nonlinear constrained optimization .

Hopfield神经网络与增广拉格朗日乘子法相结合来求解非线性约束优化。

Optimal control problems of bilinear system based on the quadratic performance index are converted into dynamic programming problems and are solved by Hopfield neural network ( HNN ) .

将基于二次型性能指标的离散双线性系统最优控制问题转化为动态规划问题，并用Hopfield神经网络（HNN）求解。

A neural network model with transient chaotic dynamic behaviors is proposed by introducing a nonlinear self-feedback into canonical Hopfield neural networks ( HNN ) .

通过在Hopfield神经网络模型（HNN）中引入非线性自反馈项，提出了一种具有暂态混沌动力学行为的神经网络模型。

Propose a multicriterion HNN neural network image reconstruction algorithm and a Genetic image reconstruction algorithm based on a few of projections of the solid rocket engine .

提出了固体火箭发动机少量投影下的多准则神经网络重建算法和遗传重建算法。

For practical design purposes , the stochastic input error estimates for the stochastic HNN with respect to the corresponding deterministic HNN is derived .

之后，为了实际设计神经网络的需要，我们对含有噪声的HNN和与其对应的一般HNN之间随机输入误差的估计进行了研究。

The validity of the derived identify scheme is proved by the simulation results of HNN based asynchronous motor drive system parameters ' identification in consider of sensors ' characteristics .

通过在鼠笼式电机传动系统参数辨识中应用的仿真结果，验证了该辨识方案的正确性。

In this detector , GA provides firstly an initial solution at first , upon which the HNN performs local optimization according to the steepest descent mechanism .

该检测器中，遗传算法首先给神经网络提供一个较好的初始解，神经网络在此基础上按梯度下降的机制进行局部寻优。

Energy function and optimization calculation theories in Hopfield Neural Network ( HNN ) are used , along with the Fourier Algorithm , achieving the accurate and fast detection of harmonic .

该方法运用了Hopfield神经网络的能量函数和优化计算原理，配合傅立叶加窗插值算法，使得神经网络和傅立叶算法有效并互补性的结合起来，达到了精确、快速检测谐波的目的。

This paper studies the robust H stability ( e.g. in the sense of Hopfield ) for Hopfield neural networks ( HNN for short ) with impulsive effects .

研究了脉冲Hopfield神经网络在Hopfield意义下的鲁棒稳定性。

The safety of the planned path was considered in the weight design of the HNN , and local virtual repulsive forces were formed around obstacles to generate safe path .

HNN权值设计中考虑了路径安全性因素，通过在障碍物附件形成局部虚拟排斥力来形成安全路径。

The paper compares the features and mechanism of Back-propagation neural networks ( BPNN ) with that of Hopfield neural networks ( HNN ), then their application effects in potential field inversion .

比较了BP、Hopfield二种神经网络模型的特性及其运行机制，分别用于位场反演，还比较了各自在位场反演中的应用效果。

With reference to the parameter estimation problem , a linearized model of the experimental mechanism is established , whose state equation is determined by means of the continuous Hopfield Neural Networks ( HNN ) .

在参数估计方面，本文构造了弹性连杆机构动力学系统的线性化模型，根据连续型Hopfield神经网络（HNN）的优化计算原理，对该线性化模型的状态方程进行了参数估计。

Based on the Crossbar switching fabrics with virtual output queuing ( VOQ ) buffers , an effective Hopfield neural network ( HNN ) based control approach for scheduling cell is proposed .

基于虚拟输出队列（VOQ）缓存的Crossbar交换结构，提出了一种Hopfield神经网络（HNN）控制的信元交换调度方法。

The second step ( recognition ) is achieved by using a holographic nearest-neighbor algorithm ( HNN ), in which vectors obtained in the preprocessing step are used as inputs to it .

第二步，识别阶段，采用了一种亲笔最近相邻算法（HNN）。

In order to effectively provide better QoS to users , a Hopfield neural network ( HNN ) is used in this paper to allocate bandwidth resources adaptively and fairly among the admitted calls .

为了给各种用户有效提供更好的服务质量，我们使用Hopfield神经网络在已接入会话间自适应和公平地分配带宽资源。

Since the Travelling Salesman Problem ( TSP ) was solved successfully by Hopfield neural network ( HNN ), the HNN series has been intensively studied and applied in various kinds of optimization problems .

自从Hopfield神经网络（HNN）成功地解决了旅行商问题（TSP）以后，HNN系列混沌神经网络被广泛地研究和应用于各种优化问题。

To deal with the path planning of mobile robot in dynamic and unknown environment , an efficient and locally connected Hopfield neural network ( HNN ) is proposed to represent the workspace of the robot .

针对动态未知环境下移动机器人路径规划问题，采用一种有效的局部连接Hopfiled神经网络（HopfieldNeuralNetworks，HNN）来表示机器人的工作空间。