Abstract A class of recurrent neural networks is developed to solve nonlinear equations, which are approximated by a multilayer perceptron (MLP). The recurrent network includes a linear Hopfield network (LHN) and the MLP as building blocks. This network inverts the original MLP using constrained linear optimization and Newton’s method for nonlinear systems. The solution of a nonlinear equation ...

Purpose We further optimized and evaluated the safety of the magnetic levator prosthesis (MLP) for temporary management of severe blepharoptosis, and compared efficacy and comfort against the ptosis crutch. Methods The interpalpebral fissure (IPF) of participants (n = 12) with ptosis was measured during attempted eyelid opening, volitional closing, and spontaneous closing with no device, ptos...

The capabilities of Locally Recurrent Neural Networks (LRNNs) in performing on-line Signal Processing (SP) tasks are well known [1,3,5,6,10,11,14,15]. In particular one of the most popular architecture is the Multi Layer Perceptron (MLP) with linear IIR temporal filter synapses (IIR-MLP) [3,5,10,11,14,15]. IIR-MLP is theoretically motivated as a non-linear generalization of linear adaptive IIR ...

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...

This paper describes incorporating discriminative features from a multi layer perceptron (MLP) into a state-of-the-art Arabic broadcast data transcription system based on cepstral features. The MLP features are based on a recently proposed Bottle-Neck architecture with long-term warped LPTRAP speech representation at the input. It is shown that the previously reported improvements on a developm...

In this paper we investigate external phone duration models (PDMs) for improving the quality of synthetic speech in hidden Markov model (HMM)-based speech synthesis. Support Vector Regression (SVR) and Multilayer Perceptron (MLP) were used for this task. SVR and MLP PDMs were compared with the explicit duration modelling of hidden semi-Markov models (HSMMs). Experiments done on an American Engl...