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The control roots of latency information theory (LIT) are reviewed in this first paper of a three papers series.
LIT is the universal guidance theory for efficient system designs that has inherently surfaced from the confluence of five
ideas. They are: 1) The source entropy and channel capacity performance bounds of Shannon's mathematical theory of
communication; 2) The latency time (LT) certainty of Einstein's relativity theory; 3) The information space (IS)
uncertainty of Heisenberg's quantum physics; 4) The black hole Hawking radiation and its Boltzmann thermodynamics
entropy S in SI J/K; and 5) The author's 1978 conjecture of a structural-physical LT-certainty/IS-uncertainty duality for
stochastic control. LIT is characterized by a four quadrants revolution with two mathematical-intelligence quadrants and
two physical-life ones. Each quadrant of LIT is assumed to be physically independent of the others and guides its
designs with an entropy if it is IS-uncertain and an ectropy if it is LT-certain. While LIT's physical-life quadrants I and
III address the efficient use of life time by physical signal movers and of life space by physical signal retainers,
respectively, its mathematical-intelligence quadrants II and IV address the efficient use of intelligence space by
mathematical signal sources and of processing time by mathematical signal processors, respectively. The theoretical and
practical relevance of LIT has already been demonstrated using real-world adaptive radar, physics and biochemistry
applications. It is the objective of this paper to demonstrate that the structural dualities that are exhibited by the four
quadrants of LIT are similar to those that were earlier identified by the author for the practical solution of stochastic
control problems. More specifically, his 1978 conjecture of a structural-physical LT-certainty/IS-uncertainty duality
between bit detection communication and deterministic quantized control problem solutions that led him to the discovery
of a Matched Processors practical alternative to Bellman's Dynamic Programming.
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