Mathematical proofs for an improvement in neural learning are presented in this paper. Within an analytical and statistical framework, dependency of neural learning on the distribution characteristic of training set vectors is established for a function approximation problem. It is shown that the BP algorithm works well for a certain type of training set vector distribution and the degree of sa...

I would like to thank Professor Hervé Bourlard, my master's thesis supervisor, who allowed me to do it at the Idiap Research Institute and who gave me a very interesting work subject: Improved Phone Posterior Estimation Through k-NN And MLP-based Similarity. I thank him, and also Dr Mathew Magimai Doss and Mrs Afsaneh Asaei for their kindness, their guidance, their availability and their suppor...

Abstract— An educational platform is presented here for the beginner students in the Simulation and Artificial Intelligence sciences. It provides with a start point of building and simulation of the manipulators, especially of 2R planar Robot. It also displays a method to replace the inverse kinematic model (IKM) of the Robot with a simpler one, by using a Multi-Layer Perceptron Neural Network ...

The main aim of this study, is to evaluate the seismic reliability of steel concentrically braced frame (SCBF) structures optimally designed in the context of performance-based design. The Monte Carlo simulation (MCS) method and neural network (NN) techniques were utilized to conduct the reliability analysis of the optimally designed SCBFs. Multi-layer perceptron (MLP) trained by back propagati...

Food production and energy consumption are two important factors when assessing greenhouse systems. The first must respond, both quantitatively qualitatively, to the needs of population, whereas latter be kept as low possible. As a result, properly control these essential aspects, appropriate environment should maintained using computational decision support system (DSS), which will especially ...

Abstract Recognizing ECG cardiac arrhythmia automatically is an essential task for diagnosing the abnormalities of muscle. The proposal few algorithms has been made classifying arrhythmias, however system classification efficiency determined on basis its prediction and diagnosis accuracy. Hence, in this study efficient as expertise. Discrete Wavelet Transform (DWT) being utilized preprocessing ...

The main challenge of the health risk assessment aerosol transport and deposition to lower airways is high computational cost. A standard large-scale airway model needs a week month time in high-performance computing system. Therefore, developing an innovative tool that accurately predicts behaviour reduces essential. This study aims develop novel machine learning (ML) predict particle airways....

Abstraet-Sammon's mapping is conventionally used for exploratory data projection, and as such is usually inapplicable for classification. In this paper we apply a neural network (NN) implementation of Sammon's mapping to classification by extracting an arbitrary number of projections. The projection map and classification accuracy of the mapping are compared with those of the auto-associative N...

Distributed Denial of Service (DDoS) attacks are still among the most dangerous on Internet. With advance methods for detecting and mitigating these attacks, crackers have improved their skills in creating new DDoS attack types with aim mimicking normal traffic behavior therefore becoming silently powerful. Among advanced types, so-called low-rate DoS at keeping a low level network traffic. In ...