The origin and structural and functional significance of modular design in organisms represent an important issue debated in many different disciplines. To be eventually successful in clarifying the evolutionary mechanisms underpinning the emergence of modular design in complex organisms, one should be able to cover all different levels of biological hierarchy. Specifically, one should be able ...

This paper presents and examines multifeature modular deep neural network acoustic models. The proposed setup uses well trained bottleneck networks to extract features from multiple combinations of input features and combines them using a classification deep neural network (DNN). The effectiveness of each feature combination is evaluated empirically on multiple test sets for both a classical DN...

This paper presents a predictive residual vector quantization (PRVQ) scheme using a modular neural network vector predictor. The proposed PRVQ scheme takes the advantage of the high prediction gain and the improved edge fidelity of a modular neural network vector predictor in order to implement a high performance vector quantization (VQ) scheme with low search complexity and a high perceptual q...

This paper focuses on the powerful concept of modularity. It is descried how this concept is deployed in natural neural networks on an architectural as well as on a functional level. Furthermore different approaches for modular neural networks are discussed. Based on this a two layer modular neural system is introduced. The basic building blocks of the architecture are multilayer Perceptrons (M...

This paper presents a Memory Neuron Network (MNN) controller for the lateral position control of a vehicle on highway in the aim to increase the traffic safety. We first present an enhanced MNN with its fast learning algorithm based on double backpropagation. Then we describe experiments achieved in collaboration with the French car manufacturer group PSA Peugeot Citroën on a XM vehicle. The pr...

Hyperspectral image (HSI) unmixing is an increasingly studied problem in various areas, including remote sensing. It has been tackled using both physical model-based approaches and more recently machine learning-based ones. In this article, we propose a new HSI algorithm combining model- techniques, based on unrolling approaches, delivering improved performance. Our approach unrolls the alterna...