Most probably, the channel model is generated by a DNN with input of the surrounding topological information, as illustrated in Figure 21. The MPA iteration is still valid because the inference DNN of ...

A linear decoder is just like a sparse autoencoder, but with a identity function as activation for the output layer, instead of the sigmoid function used by sparse autoencoders. In this way, linear ...

Consider the limitations of using the linear model, nonlinear unmixing methods have been studied under different model assumptions. However, existing nonlinear unmixing algorithms do not fully exploit ...

This dataset is being used to predict cancer mortality rate from various features such as average deaths per year, age, ethnicity, education level, income level, marital status, birth rate etc. Since ...

A DNN is a collection of multilayer perceptron's (MLPs) with a layer count >3. MLPs are a type of FFANN that are referred through the n layers that comprise them and benefit one another, as ...

A Support Vector Machine (SVM) and Linear Regression (LR) were used in Wang et al. (2019), but recognition accuracy can be improved. In recent years, deep neural networks (DNN) ( Tripathi et al., 2017 ...