Search results for "NETWORKS"
showing 10 items of 3260 documents
Consensus for networks with unknown but bounded disturbances
2009
We consider stationary consensus protocols for networks of dynamic agents. The measure of the neighbors' states is affected by unknown but bounded disturbances. Here the main contribution is the formulation and solution of what we call the $\epsilon$-consensus problem, where the states are required to converge in a target set of radius $\epsilon$ asymptotically or in finite time. We introduce as a solution a dead-zone policy that we denote as the lazy rule.
Massive Lesions Classification using Features based on Morphological Lesion Differences
2007
Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 collaboration. In the automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based on morphological lesion differences. Some classifiers as a Feed Forward Neural Network, a K-Nearest Neighbours and a Support Vector Machine are used to distinguish the pathological records from the healthy ones. The results obtained in terms of sensiti…
Analysis and simulation of creativity learning by means of artificial neural networks
2007
The paper presents a new neural network approach for analysis and simulation of creative behavior. The used concept of Dynamically Controlled Neural Gas (DyCoNG) entails a combination of Dynamically Controlled Network [Perl, J. (2004a). A neural network approach to movement pattern analysis. Human Movement Science,23, 605-620] and Growing Neural Gas (Fritzke, 1995) by quality neurons. A quality neuron reflects the rareness of a piece of information and therefore can measure the originality of a recorded activity that was assigned to the neuron during the network training. The DyCoNG approach was validated using data from a longitudinal field-based study. The creative behavior of 42 particip…
PNeuro: A scalable energy-efficient programmable hardware accelerator for neural networks
2018
Proceedings of a meeting held 19-23 March 2018, Dresden, Germany; International audience; Artificial intelligence and especially Machine Learning recently gained a lot of interest from the industry. Indeed, new generation of neural networks built with a large number of successive computing layers enables a large amount of new applications and services implemented from smart sensors to data centers. These Deep Neural Networks (DNN) can interpret signals to recognize objects or situations to drive decision processes. However, their integration into embedded systems remains challenging due to their high computing needs. This paper presents PNeuro, a scalable energy-efficient hardware accelerat…
Editorial: Neuromodulatory ascending systems: Their influence at the microscopic and macroscopic levels
2022
Brain activity and behavior are constantly changing (Puig et al., 2014; Disney, 2021). Recent studies in both animal models and humans have revealed that such variations are not random in nature but controlled through slow-acting neuromodulatory systems...
Multitasking associative networks.
2012
We introduce a bipartite, diluted and frustrated, network as a sparse restricted Boltzman machine and we show its thermodynamical equivalence to an associative working memory able to retrieve multiple patterns in parallel without falling into spurious states typical of classical neural networks. We focus on systems processing in parallel a finite (up to logarithmic growth in the volume) amount of patterns, mirroring the low-level storage of standard Amit-Gutfreund-Sompolinsky theory. Results obtained trough statistical mechanics, signal-to-noise technique and Monte Carlo simulations are overall in perfect agreement and carry interesting biological insights. Indeed, these associative network…
Le infrastrutture di telecomunicazioni: quale semplificazione amministrativa?
2009
Analisi delle ambivalenze della nozione di semplificazione riferita alle infrastrutture di telecomunicazioni
Comparative Genomics of Blattabacterium cuenoti: The Frozen Legacy of an Ancient Endosymbiont Genome
2013
Many insect species have established long-term symbiotic relationships with intracellular bacteria. Symbiosis with bacteria has provided insects with novel ecological capabilities, which have allowed them colonize previously unexplored niches. Despite its importance to the understanding of the emergence of biological complexity, the evolution of symbiotic relationships remains hitherto a mystery in evolutionary biology. In this study, we contribute to the investigation of the evolutionary leaps enabled by mutualistic symbioses by sequencing the genome of Blattabacterium cuenoti, primary endosymbiont of the omnivorous cockroach Blatta orientalis, and one of the most ancient symbiotic associa…
Role of noise in a market model with stochastic volatility
2006
We study a generalization of the Heston model, which consists of two coupled stochastic differential equations, one for the stock price and the other one for the volatility. We consider a cubic nonlinearity in the first equation and a correlation between the two Wiener processes, which model the two white noise sources. This model can be useful to describe the market dynamics characterized by different regimes corresponding to normal and extreme days. We analyze the effect of the noise on the statistical properties of the escape time with reference to the noise enhanced stability (NES) phenomenon, that is the noise induced enhancement of the lifetime of a metastable state. We observe NES ef…
Quantification of melanin and hemoglobin in humain skin from multispectral image acquisition: use of a neuronal network combined to a non-negative ma…
2012
International audience; This article presents a multispectral imaging system which, coupled with a neural network-based algorithm, reconstructs reflectance cubes. The reflectance spectra are obtained using artificial neural-netwok reconstruction which generates reflectance cubes from acquired multispectral images. Then, a blind source separation algorithm based on Non-negative Matrix Factorization is used for the decomposition of human skin absorption spectra in its main pigments: melanin and hemoglobin. The analysis is performed on reflectance spectra. The implemented source separation algorithm is based on a multiplicative coefficient upload. The goal is to represent a given spectrum as t…