For a sequence of subadditive potentials, a method of choosing state points with negative growth rates for an ergodic dynamical system was given in [5]. This paper first generalizes this result to the non-ergodic dynamics, and then proves that under some mild additional hypothesis, one can choose points with negative growth rates from a positive Lebesgue measure set, even if the system does not...

In this paper we present a technique for mapping partially observable features from multiple uncertain vantage points. The problem of concurrent mapping and localization (CML) is stated as follows. Starting from an initial known position, a mobile robot travels through a sequence of positions, obtaining a set of sensor measurements at each position. The goal is to process the sensor data to pro...

Planning and acting in a dynamic environment require distinguishing controllable and contingent events and checking the dynamic controllability of plans. Known procedures for testing the dynamic controllability assume that all contingent events are observable. Often this assumption does not hold. We consider here the general case of networks with invisible as well as observable contingent point...

This paper presents non-scan design-for-testability techniques applicable to register-transfer (RT) level data path circuits. Knowledge of high-level design information, in the form of the RT-level structure, as well as the functions of the RT-level components, is utilized to develop effective non-scan DFT techniques. Instead of conventional techniques of selecting flip-flops (FF) to make contr...

There are different structure of the network and the variables, and the process of learning Bayesian networks has a lot of different forms. The structure of the network can be unknown or known, and the variables can be observable or hidden in some or all of the data points. Consequently, there are four cases of learning Bayesian networks from data: known structure and observable variables, unkn...