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In this paper, we consider a one-dimensional random geometric graph process with the inter-nodal gaps evolving according to an exponential first order autoregressive (AR(1)) process. The transition probability matrix and stationary distribution are derived for the Markov chains in terms of network connectivity and the number of components. We characterize an algorithm for the hitting time regarding...
Biogeography-based optimization (BBO) is an evolutionary algorithm that is based on the science of biogeography. Biogeography is the study of the geographical distribution of organisms. In BBO, problem solutions are represented as islands, and the sharing of features between solutions is represented as migration between islands. This paper develops a Markov analysis of BBO, including the option of...
This paper proposes a semi-analytical framework for estimating the erasure probability in single-hop multi-relay networks. Specifically, we consider a system, in which relays do not decode the information but simply forward coded packets that have been previously received from the source. This allows for uncoordinated, low-complexity processing at the relays. We present a detailed analysis of the...
A macro-action is a typical series of useful actions that brings high expected rewards to an agent. Murata et al. have proposed an actor-critic model which can generate macro-actions automatically based on the information on state values and visiting frequency of states. However, their model has not assumed that generated macro-actions are utilized for leaning different tasks. In this paper, we extend...
In this paper, we introduce a new type of coverage for wireless sensor networks, called Directed Coverage (D-coverage). Basically, D-coverage is the coverage provided by a sensor network monitoring an area between two boundaries, through which the intruder attempts to penetrates the area. We also study how to measure the quality of D-coverage. Our first evaluation approach is a projection-based simple...
The limit theorems is one of the central questions for studying in the International Probability theory. In this paper, some strong limit theorems for Markov chains of continuous state space on a non-homogeneous tree were obtained by constructing a non-negative martingale.
Low amplitude impulsive noise measurements have been carried out in the time domain on a vehicle power line network. These measurements were made on a stationary vehicle and the motor idling. The characteristics of the measured low amplitude pulses were studied in terms of amplitude, frequency, duration and time interval between successive pulses. Stochastic models based on mathematical distribution...
Sequence labeling is concerned with processing an input data sequence and producing an output sequence of discrete labels which characterize it. Common applications includes speech recognition, language processing (tagging, chunking) and bioinformatics. Many solutions have been proposed to partially cope with this problem. These include probabilistic models (HMMs, CRFs) and machine learning algorithm...
Hidden Markov models (HMMs) are widely applied to the analysis of time-dependent data sequences, such as nonlinear signal processing, natural language processing, and bioinformatics. Training data in HMMs have two possible formats: a large set of time-dependent sequential data and an infinitely long sequence. The learning process is one of the main concerns in machine learning. For a large set of...
We describe a scheme for rate-distortion with distributed encoding in which the sources to be compressed contain a common component. We show that this scheme is optimal in some situations and that it strictly improves upon existing schemes, which do not make full use of common components. This resolves in the negative an open question regarding whether independent quantization followed by independent...
Limited lookahead control policies adapt the concept of supervisor synthesis in discrete-event systems (DES) to work for very large and/or dynamic systems. This is accomplished by considering an N-step projection of possible behaviours of the system, instead of dealing directly with the entire system. This paper builds on previous work to produce a limited lookahead algorithm that incorporates probabilistic...
This paper presents a novel two-step approach for modeling forward and backward network delays in networked control systems (NCS). The first step is to build a colored Petri net (CPN) structural model for the simulation of Ethernet based networked control systems. The modular model captures the most important features of industrial networked control systems, such as client/server input/output scanning...
A model-based evaluation of a system's design often considers to what degree components need to be available multiple times in order to reach a desired level of availability, reliability or dependability. Multiple components of the same kind then lead to models with regular structures and symmetries. In stochastic models, especially Markovian models, such regularities have been used to establish lumpability...
This paper studies quantitative model checking of infinite tree-like (continuous-time) Markov chains. These tree-structured quasi-birth death processes are equivalent to probabilistic pushdown automata and recursive Markov chains and are widely used in the field of performance evaluation. We determine time-bounded reachability probabilities in these processes - which with direct methods, i.e., uniformization,...
The method of stochastic state classes provides a new approach for the analysis of non-Markovian stochastic Petri nets, which relies on the stochastic expansion of the graph of non-deterministic state classes based on difference bounds matrix (DBM) which is usually employed in qualitative verification. In so doing, the method is able to manage multiple concurrent non-exponential (GEN) transitions...
We consider a wireless downlink shared by a dynamic population of flows. The flows of random size (bits) arrive at the base station at random times, and leave when they have been completely transmitted. The transmission rate supported by the wireless channel of each flow while the flow awaits transmission varies randomly over time and is independent of that of the other flows. The scheduling problem...
In present paper, we investigate a class of stochastic differential delay equations with Poisson jump and Markovian switching. Constructing discrete approximate solution and continuous approximate solution by means of Euler-Maruyama scheme, we show the numerical solution converges to the true solution of stochastic differential delay equations with Poisson jump and Markovian switching in the sense...
The paper proposes Markov models for the reliability analysis of the wireless sensor networks. There are presented the theoretical aspects and some of the variables that are used in the domain of fault tolerant systems. There is also presented a comparison between systems using dedicated replacements and universal replacements for defective nodes. There has been conducted a study regarding the reliability...
A longstanding problem in sequential Monte Carlo (SMC) is to mathematically prove the popular belief that resampling does improve the performance of the estimation (this of course is not always true, and the real question is to clarify classes of problems where resampling helps). A more pragmatic answer to the problem is to use adaptive procedures that have been proposed on the basis of heuristic...
In the HRL field, there are several main methods such as HAMs, options, MAXQ. These methods all rely on the theory of SMDPs. However, SMDPs does not specify how the overall task can be decomposed into a collection of subtasks. This paper introduces the concept of ldquopolicy-coupledrdquo SMDPs into HAMs. It defines the concept of HAM-decomposable and makes the relations among the HAM machine, HAM-decomposable,...
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