In this paper, we discuss some analytic properties of hyperbolic tangent function and estimate some approximation errors of neural network operators with the hyperbolic tan- gent activation function. Firstly, an equat...In this paper, we discuss some analytic properties of hyperbolic tangent function and estimate some approximation errors of neural network operators with the hyperbolic tan- gent activation function. Firstly, an equation of partitions of unity for the hyperbolic tangent function is given. Then, two kinds of quasi-interpolation type neural network operators are con- structed to approximate univariate and bivariate functions, respectively. Also, the errors of the approximation are estimated by means of the modulus of continuity of function. Moreover, for approximated functions with high order derivatives, the approximation errors of the constructed operators are estimated.展开更多
For training the present Neural Network(NN)models,the standard technique is to utilize decaying Learning Rates(LR).While the majority of these techniques commence with a large LR,they will decay multiple times over ti...For training the present Neural Network(NN)models,the standard technique is to utilize decaying Learning Rates(LR).While the majority of these techniques commence with a large LR,they will decay multiple times over time.Decaying has been proved to enhance generalization as well as optimization.Other parameters,such as the network’s size,the number of hidden layers,drop-outs to avoid overfitting,batch size,and so on,are solely based on heuristics.This work has proposed Adaptive Teaching Learning Based(ATLB)Heuristic to identify the optimal hyperparameters for diverse networks.Here we consider three architec-tures Recurrent Neural Networks(RNN),Long Short Term Memory(LSTM),Bidirectional Long Short Term Memory(BiLSTM)of Deep Neural Networks for classification.The evaluation of the proposed ATLB is done through the various learning rate schedulers Cyclical Learning Rate(CLR),Hyperbolic Tangent Decay(HTD),and Toggle between Hyperbolic Tangent Decay and Triangular mode with Restarts(T-HTR)techniques.Experimental results have shown the performance improvement on the 20Newsgroup,Reuters Newswire and IMDB dataset.展开更多
在Bounding-box及其改进方法研究中,普遍采用正方形的重叠区域的质心作为定位的结果,然而该正方形与实际无线传感器节点的通信区域模型之间存在较大差异,导致定位误差较大。针对此问题,提出一种改进的Bounding-box定位方法。该方法在定...在Bounding-box及其改进方法研究中,普遍采用正方形的重叠区域的质心作为定位的结果,然而该正方形与实际无线传感器节点的通信区域模型之间存在较大差异,导致定位误差较大。针对此问题,提出一种改进的Bounding-box定位方法。该方法在定位时,不再采用正方形的通信区域模型,而是采用圆形的通信区域模型进行定位。基于仿真数据以及采用3种典型通信环境下真实的到达信号强度指示(received signal strength indicator,RSSI)数据完成定位实验,实验结果表明,该方法具有较高的定位精度,因此具有一定的实际应用价值。展开更多
为了解决基于测距的无线传感器网络节点三维定位中可能会发生翻转模糊的问题,本文提出并证明了节点三维定位的翻转模糊检测问题,可以等价为判断是否存在一个平面和所有参考节点的测距误差球都相交的问题(Existence of Intersecting Plan...为了解决基于测距的无线传感器网络节点三维定位中可能会发生翻转模糊的问题,本文提出并证明了节点三维定位的翻转模糊检测问题,可以等价为判断是否存在一个平面和所有参考节点的测距误差球都相交的问题(Existence of Intersecting Plane,EIP).为了求解EIP问题,本文进一步提出了公切面法(Common Tangent Plane,CTP)和正交投影法(Orthogonal Projection,OP)两种求解方法.CTP方法采用的是边界检测原理,OP方法则将EIP问题转化为一个角度计算问题,并用坐标变换的方式来求解.经过理论分析和大量的仿真证明,CTP方法虽然具有较好的检测效果,但是计算复杂度太大;而OP方法在几乎获得与CTP方法相同的检测结果的情况下,能够大大降低求解EIP问题的计算复杂度.展开更多
基金Supported by the National Natural Science Foundation of China(61179041,61272023,and 11401388)
文摘In this paper, we discuss some analytic properties of hyperbolic tangent function and estimate some approximation errors of neural network operators with the hyperbolic tan- gent activation function. Firstly, an equation of partitions of unity for the hyperbolic tangent function is given. Then, two kinds of quasi-interpolation type neural network operators are con- structed to approximate univariate and bivariate functions, respectively. Also, the errors of the approximation are estimated by means of the modulus of continuity of function. Moreover, for approximated functions with high order derivatives, the approximation errors of the constructed operators are estimated.
文摘For training the present Neural Network(NN)models,the standard technique is to utilize decaying Learning Rates(LR).While the majority of these techniques commence with a large LR,they will decay multiple times over time.Decaying has been proved to enhance generalization as well as optimization.Other parameters,such as the network’s size,the number of hidden layers,drop-outs to avoid overfitting,batch size,and so on,are solely based on heuristics.This work has proposed Adaptive Teaching Learning Based(ATLB)Heuristic to identify the optimal hyperparameters for diverse networks.Here we consider three architec-tures Recurrent Neural Networks(RNN),Long Short Term Memory(LSTM),Bidirectional Long Short Term Memory(BiLSTM)of Deep Neural Networks for classification.The evaluation of the proposed ATLB is done through the various learning rate schedulers Cyclical Learning Rate(CLR),Hyperbolic Tangent Decay(HTD),and Toggle between Hyperbolic Tangent Decay and Triangular mode with Restarts(T-HTR)techniques.Experimental results have shown the performance improvement on the 20Newsgroup,Reuters Newswire and IMDB dataset.
文摘在Bounding-box及其改进方法研究中,普遍采用正方形的重叠区域的质心作为定位的结果,然而该正方形与实际无线传感器节点的通信区域模型之间存在较大差异,导致定位误差较大。针对此问题,提出一种改进的Bounding-box定位方法。该方法在定位时,不再采用正方形的通信区域模型,而是采用圆形的通信区域模型进行定位。基于仿真数据以及采用3种典型通信环境下真实的到达信号强度指示(received signal strength indicator,RSSI)数据完成定位实验,实验结果表明,该方法具有较高的定位精度,因此具有一定的实际应用价值。
