MULTIPLE-INPUT MULTIPLE-OUTPUT (MIMO) DETECTOR SELECTION USING NEURAL NETWORKA method and system for training a neural network are herein provided. According to one embodiment, a method includes generating a first labelled dataset corresponding to a first modulation scheme and a second labelled dataset...
To train a network with multiple input layers or multiple outputs, use thecombineandtransformfunctions to create a datastore that outputs a cell array with (numInputs+numOutputs) columns, wherenumInputsis the number of network inputs andnumOutputsis the number of network outputs. The firstnumIn...
a neural network nonlinear generalized predictive adaptive controller and a switching mechanism.The linear robust generalized predictive adaptive controller can ensure the bound- edness of the input and output signals in the closed-loop system and the neural network nonlinear generalized predictive adaptive...
For any detected sound source, the speaker embedding output at the estimated direction is the predicted speaker embedding. 2.3. Network Architecture Design a multi-task network for speaker embedding using DOA estimation as an auxiliary task. image-20220415200628427 The green blocks applies 2D ...
The learning is an unsupervised process which can be done on the fly without any need to have output training patterns. The clusters represent the spatial form of the map and make further analyses of the map easier and faster. Also, clusters can be interpreted as features extracted from the ...
MIMO Channel Equalization and Symbol Detection using Multilayer Neural Network In recent years Multiple Input Multiple Output (MIMO) systems have been employed in wireless communication systems to reach the goals of high data rate. A ... A Waseem,AHM Hossain 被引量: 0发表: 2013年 ...
Quadrature spatial modulation (QSM) is proposed recently as an efficient multiple-input–multiple-output wireless communication technique. In QSM, spatial multiplexing gain is achieved through modulating a two-dimensional spatial constellation diagram in addition to conventional signal modulation. It was demo...
To assess the response of lymphomas to chemotherapy, gene expression profiling data from DNA microarrays were analyzed using the fuzzy neural network (FNN)... T Ando,M Suguro,T Kobayashi,... - 《Journal of Bioscience & Bioengineering》 被引量: 125发表: 2003年 Leveraging input and output struc...
The present study used a convolutional neural network (CNN) because the image data of the elemental distributions of tribofilms were used as the input values. The CNN, which is a kind of neural network, is used to predict the output value from image data. This is because neural network mod...
可以达到 *-to-many的效果 return_state: state指的是cell里的c 默认FALSE,为TRUE时可以输出最后一个state ref有详述:https...1.常见的4中结构one to one:model.add(Dense(output_size,input_shape=input_shape)) one to many:model tensorflow图像数据预处理keras版本 ...