To avoid local minima entrapment, an adaptive backpropagation algorithm based on Lyapunov stability theory is used. Lyapunov stability theory gives the algorithm, the efficiency of attaining a single global minimum point. The learning parameters used in this algorithm is responsible for the faster ...
For this problem, the backpropagation algorithm guides the network's training. It holds the network's structure constant and modifies the weight associated with each connection. This is an iterative process that...
James McCaffrey explains how to train a DNN using the back-propagation algorithm and describes the associated 'vanishing gradient' problem. You'll get code to experiment with, and a better understanding of what goes on behind the scenes when you use a neural network library such as Microsoft CN...
Having said this, AlphaCode and similar AIs could quite quickly become very useful tools for those areas of programming that are dominated by algorithm design, and could require some rethinking of what skills are important for developers. Remember also that there have been many developments over the...
They present a stochastic learning algorithm based on simulated annealing in weight space. The convergence properties and feasibility of the algorithm are verified关键词: ieee computer society DOI: 10.1109/CMPSAC.1989.65163 被引量: 14 年份: 1989 ...
A decision algorithm based on a combination of discrete wavelet transforms (DWT) and back-propagation neural network (BPNN) is developed. Simulations and the training process for the backpropagation neural network are performed using ATP/EMTP and MATLAB. The variations of first scale high frequency ...
On the exercises and problems Using neural nets to recognize handwritten digits How the backpropagation algorithm works The Hadamard product,s⊙t Improving the way neural networks learn A visual proof that neural nets can compute any function ...
网络和反向传播算法(TheBackpropagationAlgorithm) 3.1 可微阈值单元(ADifferentiable Threshold Unit) 这里需要的单元应该是,它的输出是...一个实数值向量作为输入,计算输入的线性组合,如果结果大于某个阈值输出1,否则输出-1。 权值(weight):贡献率。 线性可分(linearlyseparable) Delta法则(delta ...
In particular, we have studied the performance of three training algorithms each from a different category of training algorithms, namely the Resilient Back Propagation method (RPROP) [19], the Adaptive On-line Back Propagation method (AOBP) [16] and the Differential Evolution algorithm (DE) [...
and the probabilitiesppare generated by Sigmoid function over these parameters. Then, we sample fromppwith Gumbel-softmax technique to get solutions and calculate objective function. Finally, we run back propagation algorithm to update parametersθθ. The whole process is briefly demonstrated in Fig....