A5057526349- Stochastic processes and statistical mechanics
- Neural dynamics and brain function
- Markov Chains and Monte Carlo Methods
- Theoretical and Computational Physics
- Neural Networks and Applications
- Algorithms and Data Compression
- Gene Regulatory Network Analysis
- Bayesian Methods and Mixture Models
- stochastic dynamics and bifurcation
- Advanced Thermodynamics and Statistical Mechanics
- Opinion Dynamics and Social Influence
- Diffusion and Search Dynamics
- Mathematical Dynamics and Fractals
- Protein Structure and Dynamics
- Speech Recognition and Synthesis
- Blind Source Separation Techniques
- Random Matrices and Applications
- Complex Network Analysis Techniques
- Natural Language Processing Techniques
- Phonetics and Phonology Research
- EEG and Brain-Computer Interfaces
- Muscle activation and electromyography studies
- Neuroscience and Music Perception
- Statistical Methods and Inference
- Sports Analytics and Performance
Universidade de São Paulo
2014-2025
Universidade Cidade de São Paulo
2024
Brazilian Society of Computational and Applied Mathematics
2008-2021
University of Victoria
2021
Hospital Universitário da Universidade de São Paulo
2021
Universidade Federal do Rio de Janeiro
2016
Brazilian Institute of Geography and Statistics
1997-2016
Universidade Federal de Uberlândia
2015
CY Cergy Paris Université
2013
Universidade Estadual de Campinas (UNICAMP)
2012
We consider dynamical systems in $\mathbb{R}^d$ driven by a vector field $b(x) = - \nabla a(x)$, where $a$ is double-well potential with some smoothness conditions. show that these when subjected to small random disturbance exhibit metastable behavior the sense defined [2]. More precisely, we prove process of moving averages along path such system converges law properly normalized jump Markov process. The main tool for our analysis theory Freidlin and Wentzell [7].
The starting point of this article is the question "How to retrieve fingerprints rhythm in written texts?" We address problem case Brazilian and European Portuguese. These two dialects Modern Portuguese share same lexicon most sentences they produce are superficially identical. Yet conjectured, on linguistic grounds, implement different rhythms. show that can be formulated as a model selection class variable length Markov chains. To carry approach, we compare texts from previously encoded...
We consider a new class of non Markovian processes with countable number interacting components, both in discrete and continuous time. Each component is represented by point process indicating if it has spike or not at given The system evolves as follows. For each component, the rate (in time) probability having depends on entire time evolution since last component. In this systems extends trivial way Spitzer's particle systems, which are Markovian, Rissanen's stochastic chains memory...
It has been classically conjectured that the brain assigns probabilistic models to sequences of stimuli. An important issue associated with this conjecture is identification classes used by perform task. We address using a new clustering procedure for sets electroencephalographic (EEG) data recorded from participants exposed sequence auditory stimuli generated stochastic chain. This indicates uses recurrent occurrences regular stimulus in order build model.
We present an upper bound on the mixing rate of equilibrium state a dynamical system defined by one-sided shift and non Hölder potential summable variations. The follows from estimation relaxation speed chains with complete connections decay, which is obtained via explicit coupling between pairs different histories.
Recently, several papers, starting with Ramus, Nespor and Mehler (1999), gave evidence that simple statistics of the speech signal could discriminate between different rhythmic classes.In present paper, we propose a new approach to problem finding acoustic correlates classes.Its main ingredient is rough measure sonority defined directly from spectrogram signal.This has major advantage it can be implemented in an entirely automatic way, no need previous hand-labelling signal.Applied same...
Stochastic chains with memory of variable length constitute an interesting family stochastic infinite order on a finite alphabet. The idea is that for each past, only suffix the called context, enough to predict next symbol. These models were first introduced in information theory literature by Rissanen (1983) as universal tool perform data compression. Recently, they have been used model up scientific areas different biology, linguistics and music. This paper presents personal introductory...
This study aims at the effects of traumatic brachial plexus lesion with root avulsions (BPA) upon organization primary motor cortex (M1). Nine right-handed patients a right BPA in whom an intercostal to musculocutaneous (ICN-MC) nerve transfer was performed had post-operative resting state fMRI scanning. The analysis empirical functional correlations between neighboring voxels revealed faster correlation decay as function distance M1 region corresponding arm compared control group. No...
In this paper we consider the class of stochastic stationary sources induced by one-dimensional Gibbs states, with Hölder continuous potentials. We show that time elapsed before source repeats its first n symbols, when suitably renormalized, converges in law either to a log-normal distribution or finite mixture exponential random variables. case also prove large deviation result.
In this paper we address the question of statistical model selection for a class stochastic models biological neural nets. Models in are systems interacting chains with memory variable length. Each chain describes activity single neuron, indicating whether it spikes or not at given time. The spiking probability neuron depends on time evolution its presynaptic neurons since last spike When spikes, potential is reset to resting level and postsynaptic current pulses generated, modifying...
We consider the one dimensional supercritical contact process with initial configurations having infinitely many particles to left of origin and only finitely its right. Starting from any such configuration, we first prove that in limit as time goes infinity law process, seen edge, converges invariant distribution constructed by Durrett [12]. then a functional central theorem for fluctuations edge around average, showing corresponding diffusion coefficient is strictly positive. finally...
A seminal paper by Rissanen, published in 1983, introduced the class of Variable Length Markov Chains and algorithm Context which estimates probabilistic tree generating chain. Even if subject was recently considered several papers, central question rate convergence remained open. This is we address here. We provide an exponential upper bound for probability incorrect estimation tree, as a function size sample. As consequence prove almost sure consistency Context. also derive bounds type I...