N eural networks are very powerful as nonlinear signal processors, but obtained results are often far from satisfactory. The purpose of this article is to evaluate the reasons for these frustrations and show how to make these neural networks successful. The following are the main challenges of neural network applications: 1) Which neural network architectures should be used? 2) How large should...

Penyakit jantung merupakan penyakit paling mematikan didunia. Laporan WHO tahun 2019 menyebutkan sebagai penyebab kematian tertinggi didunia dengan persentase 16% dari jumlah atau 8.9 juta kematian. Tingginya yang disebabkan oleh ini terjadi karena biasanya timbul tanpa adanya gejala sehingga sulit untuk diketahui sejak dini penderita. Salah satu cara mengatasi permasalahan tersebut adalah pema...

Several neural network architectures have been developed over the past several years. One of the most popular and most powerful architectures is the multilayer perceptron. This architecture will be described in detail and recent advances in training of the multilayer perceptron will be presented. Multilayer perceptrons are trained using various techniques. For years the most used training metho...

This research intends to develop a method based on the Artificial Neural Network (ANN) to predict permanent earthquake-induced deformation of the earth dams and embankments. For this purpose, data sets of observations from 152 published case histories on the performance of the earth dams and embankments, during the past earthquakes, was used. In order to predict earthquake-induced deformation o...

A new Markov-based method for real time prediction of network transmission time delays is introduced. The method considers a Multi-Layer Perceptron (MLP) neural model for the transmission network, where the number of neurons in the input layer is minimized so that the required calculations are reduced and the method can be implemented in the real-time. For this purpose, the Markov process order...

This paper presents a multi-input multi-output (MIMO) multi-layered perceptron neural network with backpropagation algorithm (MLP/BP). The proposal is a waveform equalizer for distorted nonreturn-to-zero (NRZ) data recovery in band-limited channels with co-channel interference (CCI). From the simulation results, we note that the proposed design can recover severe distorted NRZ data as well as s...

Levenberg-Marquardt algorithm and conjugate gradient method are frequently used for optimization in multi-layer perceptron (MLP). However, both algorithms have mixed conclusions optimizing MLP time series forecasting. This study uses autoregressive integrated moving average (ARIMA) with method. These methods were to predict the Air Pollutant Index (API) Malaysia's central region where represent...

In a conventional authentication process, every one may have a signature prototype that plays the role of valid benchmark. To recognize the online signature patterns, we proposed a dynamic recognition system based on a novel signature-based normalized features string (SNFS) as extracted features, and a multilayer perceptron (MLP) neural network as the classifier. We showed that the proposed SNF...

Feature extraction is one of the most important tasks in speech recognition system. Most of the speech recognition systems use Short Time Fourier Transform (STFT) for the derivation of features from the spoken utterances. In this paper we try to exploit the higher time–frequency resolution property of Discrete Wavelet Transform (DWT) for extraction of speaker independent features. The features ...

Speaker Recognition is a challenging task and is widely used in many speech aided applications. This study proposes a new Neural Network (NN) model for identifying the speaker, based on the acoustic features of a given speech sample extracted by applying wavelet transform on raw signals. Wrapper based feature selection applies dimensionality reduction by kernel PCA and ranking by Info gain. Onl...