A study of digital techniques for signal processing
Analysis and definition of digital techniques for signal processing
Engineering topics
Publications and source records attributed to Schwartz, M..
Analysis and definition of digital techniques for signal processing
A steepest descent variable step-size algorithm has been designed using dynamic programming for a mean-square-error adaptive equalizer. Additive noise and a constraint have been included. It is found that the new algorithm converges faster than the common fixed step-size algorithm.
A stochastic projected gradient algorithm is proposed which can be used for finding a constrained optimum point for a concave or convex objective function subject to nonlinear constraints which form a connected region even when only a noisy estimate of the objective function is available. For a constraint described by a single linear equation, convergence to the constrained optimum value is proved, and the rate of convergence of the algorithm to the constrained optimum value is determined. The algorithm is applied to the nonlinear problem of obtaining automatically an array of detectors which forms a beam in a desired direction in space in the presence of interfering noise so as to maximize the SNR subject to a constraint on the super-gain ratio.
Adaptive array processing, dynamic programming, digital data transmission, recursive adaptive equalizers, and finite memory communication systems
Digital techniques for adaptive signal processing
Digital signal processing, data smoothing, and computer simulation
Extremal statistics for signal and noise error probabilities estimation and computer simulation of digital feedback communication systems
Recursive techniques for digital signal processing, data smoothing and compression, and computer simulation of low error rate communication
Mood, motility, and 17-hydroxycorticoid excretion in cyclic manic-depressive patient