Surrogate Aerodynamic Wing Modeling Based on a Multilayer Perceptron

Multilayer Perceptron Based Hierarchical Acoustic Modeling for Automatic Speech Recognition

High Performance Multilayer Perceptron on a CustomComputing

Multilayer perceptrons (MLPs) are one of the most popular neural network models for solving pattern classiication and image classiication problems. Because of their ability to learn complex decision boundaries, MLPs are used in many practical computer vision applications involving classiication (or supervised segmentation). Once the connection weights in a MLP have been learnt, the network can ...

Hierarchical multilayer perceptron based language identification

Automatic language identification (LID) systems generally exploit acoustic knowledge, possibly enriched by explicit language specific phonotactic or lexical constraints. This paper investigates a new LID approach based on hierarchical multilayer perceptron (MLP) classifiers, where the first layer is a “universal phoneme set MLP classifier”. The resulting (multilingual) phoneme posterior sequenc...

Multilayer perceptron-based DFE with lattice structure

The severely distorting channels limit the use of linear equalizers and the use of the nonlinear equalizers then becomes justifiable. Neural-network-based equalizers, especially the multilayer perceptron (MLP)-based equalizers, are computationally efficient alternative to currently used nonlinear filter realizations, e.g., the Volterra type. The drawback of the MLP-based equalizers is, however,...

Aerodynamic Optimization of Transonic Wing Design Based on Evolutionary Algorithm

Evolutionary Algorithm (EA) is applied to a practical three-dimensional shape optimization for aerodynamic design of an aircraft wing. Aerodynamic performances of the design candidates are evaluated by using the three-dimensional compressive Navier-Stokes equations. A structural constraint is introduced to avoid an apparent solution of zero thickness wing for low drag in high speeds. To overcom...