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The Separation Principle
 in Stochastic Control, Redux,” http://arxiv.org/abs/1103.3005
"... ar ..."
Blind Signal Separation: Statistical Principles
, 2003
"... Blind signal separation (BSS) and independent component analysis (ICA) are emerging techniques of array processing and data analysis, aiming at recovering unobserved signals or `sources' from observed mixtures (typically, the output of an array of sensors), exploiting only the assumption of mut ..."
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Cited by 529 (4 self)
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Blind signal separation (BSS) and independent component analysis (ICA) are emerging techniques of array processing and data analysis, aiming at recovering unobserved signals or `sources' from observed mixtures (typically, the output of an array of sensors), exploiting only the assumption
The Separation Principle in Linear Regression
"... In linear regression problems in which an independent variable is a total of two or more characteristics of interest, it may be possible to improve the fit of a regression equation substantially by regressing against one of two separate components of this sum rather than the sum itself. As motivatio ..."
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Cited by 1 (0 self)
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. As motivation for this "separation principle," we provide necessary and sufficient conditions for an increased coefficient of determination. In teaching regression analysis, one might use an example such as the one contained herein, in which the number of wins of Major League Baseball teams
The Separation Principle – A Principle for Programming Language Design
, 2013
"... The separation principle: a principle for programming language design ..."
Joint design and separation principle for opportunistic spectrum access
 IEEE Transactions on Information Theory
, 2006
"... Abstract — This paper develops optimal strategy for opportunistic spectrum access (OSA) by integrating the design of spectrum sensor at the physical layer with that of spectrum sensing and access policies at the medium access control (MAC) layer. The design objective is to maximize the throughput of ..."
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Cited by 137 (35 self)
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of secondary users while limiting their probability of colliding with primary users. By exploiting the rich structures of the problem, we establish a separation principle: the design of spectrum sensor and access policy can be decoupled from that of sensing policy without losing optimality. This separation
ON THE SEPARATION PRINCIPLE OF QUANTUM CONTROL
, 2005
"... It is well known that continuous quantum measurements and nonlinear filtering can be developed within the framework of the quantum stochastic calculus of HudsonParthasarathy. The addition of realtime feedback control has been discussed by many authors, but never in a rigorous way. Here we introdu ..."
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Cited by 11 (2 self)
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introduce the notion of a controlled quantum flow, where feedback is taken into account by allowing the coefficients of the quantum stochastic differential equation to be adapted processes in the observation algebra. We then prove a separation theorem for quantum control: the admissible control
Sparse Separation: Principles and Tricks
"... Blind separation of linearly mixed white Gaussian sources is impossible, due to rotational symmetry. For this reason, all blind separation algorithms are based on some assumption concerning the fashion in which the situation departs from that insoluble case. Here we discuss the assumption of sparse ..."
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Blind separation of linearly mixed white Gaussian sources is impossible, due to rotational symmetry. For this reason, all blind separation algorithms are based on some assumption concerning the fashion in which the situation departs from that insoluble case. Here we discuss the assumption
Revisiting the Separation Principle in Stochastic Control
"... Abstract—The separation principle is the statement that under suitable conditions the design of stochastic control can be divided into two separate problems, one of optimal control with state information and one of filtering. The literature over the past 50 years contains several derivations where s ..."
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Abstract—The separation principle is the statement that under suitable conditions the design of stochastic control can be divided into two separate problems, one of optimal control with state information and one of filtering. The literature over the past 50 years contains several derivations where
Information flow and cooperative control of vehicle formations.
 In Proceeings of 15th IFAC Conference,
, 2002
"... Abstract We consider the problem of cooperation among a collection of vehicles performing a shared task using intervehicle communication to coordinate their actions. We apply tools from graph theory to relate the topology of the communication network to formation stability. We prove a Nyquist crite ..."
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Cited by 551 (11 self)
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to be used for cooperative motion. We prove a separation principle that states that formation stability is achieved if the information flow is stable for the given graph and if the local controller stabilizes the vehicle. The information flow can be rendered highly robust to changes in the graph, thus
ON THE PIONEONE SEPARATION PRINCIPLE
, 2007
"... We study the proof theoretic strength of the Π 1 1separation axiom scheme. We show that Π 1 1separation lies strictly in between the ∆ 1 1comprehension and Σ 1 1choice axiom schemes over RCA0. ..."
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Cited by 1 (1 self)
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We study the proof theoretic strength of the Π 1 1separation axiom scheme. We show that Π 1 1separation lies strictly in between the ∆ 1 1comprehension and Σ 1 1choice axiom schemes over RCA0.
Results 1  10
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5,448