Results 21 to 30 of about 1,070 (159)

Informational and Causal Architecture of Continuous-time Renewal and Hidden Semi-Markov Processes

CoRR, 2016
We introduce the minimal maximally predictive models (ε-machines) of processes generated by certain hidden semi-Markov models. Their causal states are either hybrid discrete-continuous or continuous random variables and causal-state transitions are described by partial differential equations.
Marzen, Sarah E., Crutchfield, James P.
openaire   +3 more sources

Limit theorems for semi-Markov processes [PDF]

, 1978
A new construction of regeneration times is exploited to prove ergodic and renewal theorems for semi-Markov processes on general state spaces. This work extends results of the authors in Ann. Probability (6 (1978), 788-797)
Neya, P. E., Athreya, K. B.
core   +1 more source

The Class of Semi-Markov Accumulation Processes [PDF]

, 2017
In conjunction with the 15th International Conference of Numerical Analysis and Applied Mathematics (ICNAAM 2017)International audienceIn this paper, we introduce a new accumulation process, the Semi-Markov Accumulation Process (SMAP).
Alain Jean-Marie, Vatamidou, Eleni, Jean-Marie, Alain, Eleni Vatamidou   +3 more
core   +1 more source

Full‐Stack Architectures for Intelligent Brain‐Computer Interfaces

Advanced Science, EarlyView.
System‐level overview of brain–computer interfaces (BCIs), illustrating the integration of neural signal acquisition, wireless transmission, and adaptive decoding. Advanced electrode, tissue interfaces, energy‐efficient communication, and robust algorithms collectively enable stable signal quality, real‐time processing, and closed‐loop operation ...
Hee Kyu Lee, Hyun Bin Kim, Sang Uk Park, Janghoon Joo, Jinhong Min, Geumbee Lee, Joohoon Kang, Hyoyoung Jeong, Jae‐Young Yoo, Sang Min Won   +9 more
wiley   +1 more source

Semi-Markov processes and α-invariant distributions

, 1977
A semi-Markov process is easily made Markov by adding some auxiliary random variables. This paper discusses the I-type quasi-stationary distributions of such “extended” processes, and the α-invariant distributions for the corresponding Markov transition ...
Arjas, E., Nummelin, E.
core   +1 more source

Variance bounding and geometric ergodicity of Markov chain Monte Carlo kernels for approximate Bayesian computation [PDF]

, 2014
Approximate Bayesian computation has emerged as a standard computational tool when dealing with intractable likelihood functions in Bayesian inference. We show that many common Markov chain Monte Carlo kernels used to facilitate inference in this setting
Łatuszyński, Krzysztof, Lee, Anthony
core   +1 more source

The simple harmonic urn

, 2011
We study a generalized Polya urn model with two types of ball. If the drawn ball is red it is replaced together with a black ball, but if the drawn ball is black it is replaced and a red ball is thrown out of the urn.
Crane, E., Georgiou, Nicholas, Waters, Robert J., Stanislav Volkov, Crane, ET, Volkov, S, Wade, Andrew R., Georgiou, N, Andrew R. Wade, Volkov, Stanislav,, Waters, R.J., Nicholas Georgiou, Robert J. Waters, Wade, Andrew, Crane, Edward, Georgiou, N., Edward Crane, Waters, RJ, Georgiou, Nicolas, Wade, AR, Volkov, Stanislav, Lund University.   +21 more
core   +1 more source

COVARIANCE MATRIX OF MULTIVARIATE REWARD PROCESSES WITH NONLINEAR REWARD FUNCTIONS [PDF]

Journal of Sciences, Islamic Republic of Iran, 2003
Multivariate reward processes with reward functions of constant rates, defined on a semi-Markov process, first were studied by Masuda and Sumita, 1991. Reward processes with nonlinear reward functions were introduced in Soltani, 1996.
doaj  

Rethinking areas of endemism and barriers: perspectives for a causal historical biogeography and a critique of Schultz and Cracraft (2024)

Cladistics, EarlyView.
Abstract Historical biogeography faces a persistent conceptual and methodological dilemma concerning the nature of its central analytical units. Using the recent proposal by Schultz and Cracraft (Cladistics 40, 653) as a catalyst, this article critiques the argument that causal inference necessitates the replacement of areas of endemism with barriers ...
Augusto Ferrari
wiley   +1 more source

Optimal policies for discrete time risk processes with a Markov chain investment model [PDF]

, 2006
We consider a discrete risk process modelled by a Markov Decision Process. The surplus could be invested in stock market assets. We adopt a realistic point of view and we let the investment return process to be statistically dependent over time.
Romera, Rosario, Diasparra, Maikol
core