Downscaling global weather prediction model outputs to individual locations or local scales is a common practice for operational weather forecast in order to correct the model outputs at subgrid scales. This paper presents an empirical-statistical downscaling method for precipitation prediction which uses a feed-forward multilayer perceptron MLP neural network. The MLP architecture was optimize...

A method for combining dynamic force and static position measurements for the monitoring of assembly is presented. A multilayer perceptron (MLP) network is used as a classiier where the individual network outputs correspond to contact state transitions occuring during the assembly process. When a contact state transition occurs, the MLP output with the largest value is chosen. The recognised co...

We describe a system that localizes a single dipole to reasonable accuracy from noisy magnetoencephalographic (MEG) measurements in real time. At its core is a multilayer perceptron (MLP) trained to map sensor signals and head position to dipole location. Including head position overcomes the previous need to retrain the MLP for each subject and session. The training dataset was generated by ma...

The Artificial Neural Network (ANN) Multilayer Perceptron (MLP) has shown good performance levels as discriminant system in text-independent Speaker Verification (SV) tasks, as shown in our work presented at Eurospeech 2001. In this paper, substantial improvements with regard to that reference architecture are described. Firstly, a new heuristic method for selecting the impostors in the ANN tra...

− This paper describes a neural network system for power electric load forecasting of telecommunication station. Getting an accuracy useful for contractual purpose a separately daily forecast of both main load and its oscillation is proposed. For the mean daily forecast we used a three layers multilayer perceptron (MLP), while to the oscillation forecasting we realized a system composed by a ML...

In a speaker-independent, large-vocabulary continuous speech recognition systems, recognition accuracy varies considerably from speaker to speaker, and performance may be significantly degraded for outlier speakers such as nonnative talkers. In this paper, we explore supervised speaker adaptation and normalization in the MLP component of a hybrid hidden Markov model/ multilayer perceptron versi...

In this paper, a new neural network paradigm and its application to recognition of speech patterns is presented. The novel NN paradigm is a multilayer version of the well-known LVQ algorithm from Kohonen. The approach includes the following innovations and improvements compared to other popular neural network paradigms: 1) It is according to the knowledge of the author the first multilayer vers...

The traffic safety of mountain highway has always been one the taking point. This study aims to collect road design data in large-scale research and analyzes accident risk geometric alignment. Accordingly, a method based on satellite maps clustering algorithms is proposed calculate alignment plane its longitudinal section. reliability was verified Nanfu Chongqing, China. planar sectional geomet...

Speaker recognition is the process of automatically recognizing who is speaking on the basis of individual information included in speech waves. Feature extraction for speech recognition is a subject of a major interest today; different features have been investigated in speech recognition systems. The perceptual linear predictive PLP: this technique uses three concepts from the psychophysics o...

In the paper we present two techniques improving the recognition accuracy of multilayer perceptron neural networks (MLP ANN) by means of adopting Speaker Adaptive Training. The use of the MLP ANN, usually in combination with the TRAPS parametrization, includes applications in speech recognition tasks, discriminative features production for GMM-HMM and other. In the first SAT experiments, we use...