The multilayer perceptron (MLP) is a well established neural network model for supervised learning problems. Furthermore, it is well known that its performance for a given problem depends crucially on appropriately selecting the MLP architecture, which is typically achieved using cross-validation. In this work, we propose an incremental Bayesian methodology to address the important problem of a...

This paper 1 proposes a method to extract nonlinear discriminant features from given input measurements by using outputs of multilayer Perceptron (MLP). Linear Discriminant Analysis (LDA) is one of the best known methods to construct linear features which are suitable for class discrimination. Otsu showed that LDA can be extended to nonlinear if we can estimate Bayesian a posteriori probabiliti...

In recent years, the cryptographic community has explored new approaches of power analysis based on machine learning models such as Support Vector Machine (SVM), MultiLayer Perceptron (MLP) or Random Forest (RF). Realized experiments proved that the method based on MLP can provide almost 100% success rate after optimization. Nevertheless, this description of results is based on the first order ...

Two-step physical register deallocation (TSD) is an architectural scheme that enhances memory-level parallelism (MLP) by preexecuting instructions. Ideally, TSD allows exploitation of MLP under an unlimited number of physical registers, and consequently only a small register file is needed for MLP. In practice, however, the amount of MLP exploitable is limited, because there are cases where eit...

The Minimum Length Polygon (MLP) is an interesting first order approximation of a digital contour. For instance, the convexity of the MLP is characteristic of the digital convexity of the shape, its perimeter is a good estimate of the perimeter of the digitized shape. We present here two novel equivalent definitions of MLP, one arithmetic, one combinatorial, and both definitions lead to two dif...

We describe the development of a speech recognition system for conversational telephone speech (CTS) that incorporates acoustic features estimated by multilayer perceptrons (MLP). The acoustic features are based on frame-level phone posterior probabilities, obtained by merging two different MLP estimators, one based on PLP-Tandem features, the other based on hidden activation TRAPs (HATs) featu...

Leakage current is a key factor in IC power consumption even in the active operating mode. We investigate the simultaneous optimization of gate size and threshold voltage to reduce leakage power. We assume a standard-cell-based design flow where the available cell sizes and threshold voltages (V t 's) are given, and model the optimization as a mixed-integer linear programming (MLP) problem. In ...

MLP based front-ends have shown significant complementary properties to conventional spectral features. As part of the DARPA GALE program, different MLP features were developed for Mandarin ASR. In this paper, all the proposed frontends are compared in systematic manner and we extensively investigate the scalability of these features in terms of the amount of training data (from 100 hours to 16...

We studied adipocytes from 8-week-old control rat offspring (CON) or rat offspring subjected to maternal low (8%) protein (MLP) feeding during pregnancy/lactation, a procedure predisposing to obesity. Acute exposure to isoproterenol or adenosine enhanced PDK4 and PPARγ mRNA gene expression in CON and MLP adipocytes. Enhanced adipocyte Pdk4 expression correlated with increased PPARγ expression. ...

This study aims to develop a generalized framework of an SOM called a modular network SOM (mnSOM). The mnSOM has an array structure consisting of functional modules that are trainable neural networks, e.g., multi-layer perceptrons (MLPs), instead of the vector units of the conventional SOM. In the case of MLP-modules, an mnSOM learns a group of systems or functions in terms of the input-output ...