Extreme Learning Machine (ELM) is a new learning method for single-hidden layer feedforward neural network (SLFN) training. ELM approach increases the learning speed by means of randomly generating input weights and biases for hidden nodes rather than tuning network parameters, making this approach much faster than traditional gradient-based ones. However, ELM random generation may lead to nono...

In this paper, we show that applying a machine learning technique called auto-decoder (AD) to high-rate and short length Reed–Muller (RM) decoding enables it achieve maximum likelihood (MLD) performance faster speed than when fast Hadamard transform (FHT) is applied in additive white Gaussian noise (AWGN) channels. The approximately 1.8 times 125 the FHT for R(1,4) R(2,4), respectively. number ...

In an aging global society, a few complex problems have been occurring due to falls among the increasing elderly population. Therefore, are detected using pendant-type sensor that can be worn comfortably for fall detection. The sensed data processed by embedded environment and classified long-term memory (LSTM). A detection system combines simple threshold method (STM) LSTM, STM-LSTM-based syst...

In this paper, the gain in LD-CELP speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (PSO) algorithms to optimize the structure and parameters of neural networks. Elman, multi-layer perceptron (MLP) and fuzzy ARTMAP are the candidate neural models. The optimized number of nodes in the first and second hidden layers of El...

the goal of this study was to predict the moisture content of paddy using machine vision and artificial neural networks (anns). the grains were dried as thin layer with air temperatures of 30, 40, 50, 60, 70, and 80°c and air velocities of 0.54, 1.18, 1.56, 2.48 and 3.27 ms-1. kinetics of l*a*b* were measured. the air temperature, air velocity, and l*a*b* values were used as ann inputs. the res...

Groundwater quality management is the most important issue in many arid and semi-arid countries, including Iran.Artificial neural network (ANN) has an extensive range of applications in water resources management. In this study,artificial neural network was developed using MATLAB R2013 software package, and Cl, EC, SO4 and NO3 qualitativeparameters were estimated and compared with the measured ...

Since the pioneering work by White (1988), the application of artiicial neural networks (ANNs) to nance has enjoyed an exponential growth in research and publications. The evidences accumulated over the last decade indicate that the success of the nancial application of ANNs crucially depends on the design of the ANN. Let us rst consider the structure of the ANN. It is well known that nonlinear...

To infer a multilayer representation of high-dimensional count vectors, we propose the Poisson gamma belief network (PGBN) that factorizes each of its layers into the product of a connection weight matrix and the nonnegative real hidden units of the next layer. The PGBN’s hidden layers are jointly trained with an upward-downward Gibbs sampler, each iteration of which upward samples Dirichlet di...

This paper presents neural network (NN) control of planar four-legged walking robot. The control system consists of a neural controller, standard PD controller and walking robot. Proposed NN is employed as an inverse controller of the robot. In addition to feedforward connections from the input layer to the hidden layer and from the hidden layer to the output layer, there is also feedback conne...

forecasting of temperature is a very important in meteorology. air temperature prediction is of a concern in environment, industry and agriculture. temperature with precipitation are important factors in meteorology and are used in classification of climate. in this paper we want to predict average monthly temperature for chosen station of isfahan province. an artificial neural network is a pow...