New activation functions for single layer feedforward neural networkArtificial Neural NetworkActivation functionGeneralized swishReLU-swishTriple-state swishArtificial Neural Network (ANN) is a subfield of mach
We prove a negative result for the approximation of functions defined on compact subsets of Rd (where d≥2) using feedforward neural networks with one hidden layer and arbitrary continuous activation function. In a nutshell, this result claims the existence of target functions that are as difficul...
Learning in Single Hidden‐Layer Feedforward Network Models: Backpropagation in a Spatial Interaction Modeling Context. Geographical Analysis, 28(1), pp.38-55.Gopal S, Fischer M M, 1996, "Learning in single hidden-layer feedforward network models" Geographical Analysis 28 (1) 38 - 55...
In this paper, we propose a multi-criteria decision making based architecture selection algorithm for single-hidden layer feedforward neural networks trained by extreme learning machine. Two criteria are incorporated into the selection process, i.e., training accuracy and the Q-value estimated by ...
{c}\), these embeddings can be used as inputs for prediction tasks. During pretraining, a linear projection function was applied to the embeddings to predict the probabilities of the masked nodes. In the fine-tuning step, we utilized a single-layer feed-forward network with a softmax ...
These virtual neurons receive random projections from the input layer containing the information to be processed. One key advantage of this approach is that it can be implemented efficiently in hardware. We show that the reservoir computing implementation, in this case optoelectronic, is also capable...
Backbone Network:VGG-16 和ResNet-101,在ILSVRC CLS-LOC上预训练过。 Anchors Design and Matching:为了处理不同物体的scale, 选择了四层feature layers以8,16,32,64的stride. 每个feature layer与anchor特定scale联结。先以最好overlap score来match groud truth和anchor box, 然后match其他ground truth (overlap>...
Similarly, each arrow can be seen as picking up a number from a node, performing a weighted computation on it, and carrying it forward to the next layer of nodes: Now, we have a neural network with one hidden layer. We call this a hidden layer as the state of this layer is not ...
dropping monotonically from 74.3 to 62.4. When we stack boxes of multiple scales on a layer, many are on the image boundary and need to be handled carefully. We tried the strategy used in Faster R-CNN [2], ignoring boxes which are on the boundary. We observe some interesting trends. For...
A design scheme of an adaptive trajectory linearization control system for an aerospace vehicle was presented by usingsingle hidden layer neural networks(SHLNN). 利用单隐层神经网络的逼近能力在线估计系统中存在的不确定性,神经网络输出用以抵消不确定性对轨迹线性化方法控制性能的影响。