Crocodylian Snouts in Space and Time: Phylogenetic Approaches Toward Adaptive Radiation1

Toward A Portable Parallel Library for Space-Time Adaptive Methods

Space-time adaptive processing (STAP) refers to a class of methods for detecting targets using an array of sensors. The output of the array is weighted using data collected from the sensors over a given period of time. An optimal method of calculating weights exists: however, this method is usually computationally impractical. Therefore, various heuristic methods are used that approximate the o...

Discrete time robust control of robot manipulators in the task space using adaptive fuzzy estimator

This paper presents a discrete-time robust control for electrically driven robot manipulators in the task space. A novel discrete-time model-free control law is proposed by employing an adaptive fuzzy estimator for the compensation of the uncertainty including model uncertainty, external disturbances and discretization error. Parameters of the fuzzy estimator are adapted to minimize the estimat...

Toward accurate dynamic time warping in linear time and space

ion speeds up the DTW algorithm by operating on a reduced representation of the data. These algorithms include IDDTW [3], PDTW [13], and COW [2] . The left side of Figure 5 shows a full-resolution cost matrix for which a minimum-distance warp path must be found. Rather than running DTW on the full resolution (1/1) cost matrix, the time series are reduced in size to make the number of cells in t...

Space-time adaptive processing

Space-Time Adaptive Processing: Fundamentals

In this lecture, we present the principles of space-time adaptive processing (STAP) for radar, applied to moving target indication. We discuss the properties of optimum STAP, as well as problems associated with estimating the adaptive weights not encountered with spatial-only processing (i.e. beamforming).