Pattern reconstruction and sequence processing in feed-forward layered neural networks near saturation

The dynamics and the stationary states for the competition between pattern reconstruction and asymmetric sequence processing are studied here in an exactly solvable feed-forward layered neural network model of binary units and patterns near saturation. Earlier work by Coolen and Sherrington on a parallel dynamics far from saturation is extended here to account for finite stochastic noise due to a Hebbian and a sequential learning rule. Phase diagrams are obtained with stationary states and quasi-periodic non-stationary solutions. The relevant dependence of these diagrams and of the quasi-periodic solutions on the stochastic noise and on initial inputs for the overlaps is explicitly discussed.Comment: 9 pages, 7 figure

Instability of frozen-in states in synchronous Hebbian neural networks

The full dynamics of a synchronous recurrent neural network model with Ising binary units and a Hebbian learning rule with a finite self-interaction is studied in order to determine the stability to synaptic and stochastic noise of frozen-in states that appear in the absence of both kinds of noise. Both, the numerical simulation procedure of Eissfeller and Opper and a new alternative procedure that allows to follow the dynamics over larger time scales have been used in this work. It is shown that synaptic noise destabilizes the frozen-in states and yields either retrieval or paramagnetic states for not too large stochastic noise. The indications are that the same results may follow in the absence of synaptic noise, for low stochastic noise.Comment: 14 pages and 4 figures; accepted for publication in J. Phys. A: Math. Ge

Period-two cycles in a feed-forward layered neural network model with symmetric sequence processing

The effects of dominant sequential interactions are investigated in an exactly solvable feed-forward layered neural network model of binary units and patterns near saturation in which the interaction consists of a Hebbian part and a symmetric sequential term. Phase diagrams of stationary states are obtained and a new phase of cyclic correlated states of period two is found for a weak Hebbian term, independently of the number of condensed patterns $c$.Comment: 8 pages and 5 figure

Symmetric sequence processing in a recurrent neural network model with a synchronous dynamics

The synchronous dynamics and the stationary states of a recurrent attractor neural network model with competing synapses between symmetric sequence processing and Hebbian pattern reconstruction is studied in this work allowing for the presence of a self-interaction for each unit. Phase diagrams of stationary states are obtained exhibiting phases of retrieval, symmetric and period-two cyclic states as well as correlated and frozen-in states, in the absence of noise. The frozen-in states are destabilised by synaptic noise and well separated regions of correlated and cyclic states are obtained. Excitatory or inhibitory self-interactions yield enlarged phases of fixed-point or cyclic behaviour.Comment: Accepted for publication in Journal of Physics A: Mathematical and Theoretica

Transition between localized and extended states in the hierarchical Anderson model

We present strong numerical evidence for the existence of a localization-delocalization transition in the eigenstates of the 1-D Anderson model with long-range hierarchical hopping. Hierarchical models are important because of the well-known mapping between their phases and those of models with short range hopping in higher dimensions, and also because the renormalization group can be applied exactly without the approximations that generally are required in other models. In the hierarchical Anderson model we find a finite critical disorder strength Wc where the average inverse participation ratio goes to zero; at small disorder W < Wc the model lies in a delocalized phase. This result is based on numerical calculation of the inverse participation ratio in the infinite volume limit using an exact renormalization group approach facilitated by the model's hierarchical structure. Our results are consistent with the presence of an Anderson transition in short-range models with D > 2 dimensions, which was predicted using renormalization group arguments. Our finding should stimulate interest in the hierarchical Anderson model as a simplified and tractable model of the Anderson localization transition which occurs in finite-dimensional systems with short-range hopping.Comment: 7 pages, 7 figure

Spectra of sparse non-Hermitian random matrices: an analytical solution

We present the exact analytical expression for the spectrum of a sparse non-Hermitian random matrix ensemble, generalizing two classical results in random-matrix theory: this analytical expression forms a non-Hermitian version of the Kesten-Mckay law as well as a sparse realization of Girko's elliptic law. Our exact result opens new perspectives in the study of several physical problems modelled on sparse random graphs. In this context, we show analytically that the convergence rate of a transport process on a very sparse graph depends upon the degree of symmetry of the edges in a non-monotonous way.Comment: 5 pages, 5 figures, 12 pages supplemental materia

A dynamical trichotomy for structured populations experiencing positive density-dependence in stochastic environments

Positive density-dependence occurs when individuals experience increased survivorship, growth, or reproduction with increased population densities. Mechanisms leading to these positive relationships include mate limitation, saturating predation risk, and cooperative breeding and foraging. Individuals within these populations may differ in age, size, or geographic location and thereby structure these populations. Here, I study structured population models accounting for positive density-dependence and environmental stochasticity i.e. random fluctuations in the demographic rates of the population. Under an accessibility assumption (roughly, stochastic fluctuations can lead to populations getting small and large), these models are shown to exhibit a dynamical trichotomy: (i) for all initial conditions, the population goes asymptotically extinct with probability one, (ii) for all positive initial conditions, the population persists and asymptotically exhibits unbounded growth, and (iii) for all positive initial conditions, there is a positive probability of asymptotic extinction and a complementary positive probability of unbounded growth. The main results are illustrated with applications to spatially structured populations with an Allee effect and age-structured populations experiencing mate limitation

Effet d’un programme d’activité physique intermittent de haute intensité sur la perte de masse grasse abdominale chez la femme DT2 ménopausée

Contexte : A la ménopause, la diminution des taux d’estrogènes favorise un dépôt de masse grasse (MG) abdominal (sous-cutané et viscéral). La MG viscérale est corrélée aux maladies cardio-vasculaires (MCV). Ce risque est accentué chez les sujets présentant un diabète de type 2 (DT2).Objectif : Comparer deux modalités d’entraînement, continu de moyenne intensité (SSE) vs. intermittent de haute intensité (HIIE), sur la perte de MG abdominale (dont viscérale) chez des femmes DT2 ménopausées.Matériels et méthode : Seize femmes DT2 ménopausées (69±1ans; IMC : 31±1 kg/m²) ont été réparties aléatoirement en deux groupes. Pendant quatre mois, deux fois par semaine, 8 d’entre elles ont réalisé un entraînement SSE (40 min de pédalage à 50% de la FCmax de réserve), et 8 ont réalisé un entraînement HIIE (8s de sprint suivies de 12s de récupération active, pendant 20 min). Pré (T0) et post entraînement (T4), la composition corporelle et la MG abdominale totale ont été mesurées par DXA (Dual Energy X-ray Absorptiometry). La MG viscérale a été estimée à partir de la méthode de Martin et Jensen1. A T0 et T4, les apports énergétiques et le niveau d’activité physique ont été déterminés (questionnaires et accéléromètrie validée2 intégrée sur smartphone).Résultats : Après 16 semaines d’intervention, sans modification des apports énergétiques et du niveau d’activité physique total, une perte de MG totale et un gain de masse maigre est observé (effet temps, p<0.05). La diminution de MG abdominale est supérieure dans le groupe HIIE (0.32% ± 2.07 vs 8.32 % ± 2.19, p<0.05) et la perte de MG viscérale n’est observée que dans le groupe HIIE (p<0.05).Conclusion : L’entraînement de type HIIE apparait comme un programme alternatif intéressant chez la femme DT2 ménopausée en diminuant significativement la MG abdominale totale et viscérale