Abstract
Quantum Neurodynamics (QND) is a top-down approach to the modeling and simulation of neural observers and controllers. At the top is the mathematical theory of stochastic filtering, which is concerned with the transformation of observation time series into estimates of the state of the observed system. Working down toward biological neural systems entails the use of the time-dependent Schroedinger equation to compute the controllable probability density function that is essential for any stochastic filter. Unlike the Kaiman filter, this QND filter is computable on a neural lattice and it comprehends the dynamics of arbitrary Hamiltonian systems evolving under time-varying force fields. Applications of QND include image tracking, speech recognition, control of nonlinear systems, the solution of problems in quantum mechanics and the modeling of neural and cognitive processes.
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