Accession Number ADA573423
Title Engineering Awareness.
Publication Date Feb 2010
Media Count 4p
Personal Author G. V. Cybenko V. Crespi
Abstract Generalized Process Tracking. Defined a rigorous concept of 'trackability' of processes in a distributed sensing system. Established fundamental properties of processes and sensing infrastructure that are necessary and sufficient for certain types of trackability to be feasible. Problem addressed and solved: determine the 'complexity' of estimating state trajectories of a target process based on a discrete-time sequence of noisy 'observations'. Conducted a comparative analysis of design methodologies for Agent-Based Systems. Machine Learning complex processes from data: discovery of a new algorithm to learn Hidden Markov Models (HMMs) from typical realizations of the associated stochastic process. The new method is based on the non- negative matrix factorization (NMF) of higher order Markovian statistics and is structurally different from the classical Baum-Welsh and associated approaches. Cognitive Complexification: development of new methods to shape network communications for preventing covert transmissions from hiding behind the statistics of ordinary traffic.
Keywords Covert channels
Covert communications
Distributed control
Hidden markov models
Machine learning
Markov processes
Monitoring
Multi-agent systems
Probabilistic automata
Sensor systems
Situational awareness
Stochastic processes
Target tracking
Trackability

 
Source Agency Non Paid ADAS
NTIS Subject Category 72F - Statistical Analysis
Corporate Author California State Univ., Los Angeles.
Document Type Technical report
Title Note Final rept. 1 May 2007-30 Nov 2009.
NTIS Issue Number 1317
Contract Number FA9550-07-1-0421

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