A nonlinearity is required before matched filtering in mInimum error receivers when additive noise is present which is impulsive and highly non-Gaussian. Experiments were performed to determine whether the correct clipping nonlinearity could be provided by a single-input singleoutput multi-layer perceptron trained with back propagation. It was found that a multi-layer perceptron with one input ...

the discharge or runoff which ousts from a watershed is important. because its deficiency leads to financial losses and its excesses cause damage in lives and property as flood. in this research using artificial neural network multi-layer perceptron (mlp (and adaptive neuro-fuzzy interface system (anfis) and multiple regression method simulated rainfall- runoff process on daily basis in the kho...

Recently, many convolutional neural network (CNN)-based methods have been proposed to tackle the classification task of hyperspectral images (HSI). In fact, CNN has become de-facto standard for HSI classification. It seems that traditional networks such as multi-layer perceptron (MLP) are not competitive However, in this study, we try prove MLP can achieve good performance if it is properly des...

For improving the system performance of mobile Internet, how to provide the Quality of Experience (QoE) guarantee is an important factor. First, based on artificial neural network and adaptive cross-layer perceptron, we studied the cloudassisted QoE guarantee mechanism. Then, according to the power, we divided the distance and perceptron layers of mobile Internet and cloud into three levels. We...

In this paper, an automatic system is presented for word recognition using real Turkish word signals. This paper especially deals with combination of the feature extraction and classification from real Turkish word signals. A Discrete Wavelet Neural Network (DWNN) model is used, which consists of two layers: discrete wavelet layer and multi-layer perceptron. The discrete wavelet layer is used f...

One may argue that the simplest type of neural networks beyond a single perceptron is an array of several perceptrons in parallel. In spite of their simplicity, such circuits can compute any Boolean function if one views the majority of the binary perceptron outputs as the binary output of the parallel perceptron, and they are universal approximators for arbitrary continuous functions with valu...