-We develop a method of performing pattern recognition (discrimination and classification) using a recursive technique derived from mixture models, kernel estimation and stochastic approximation. Unsupervised learning Density estimation Kernel estimator Mixture model Stochastic approximation Recursive estimation

In this paper, we modify the robust local image estimation method of R. van den Boomgaard and J. van de Weijer for the approximation of scattered data. The derivation of our knot and data dependent approximation method is based on the relation between the Gaussian facet model in image processing and the moving least square technique known from approximation theory. Numerical examples demonstrat...

While American calls on non-dividend-paying stocks may be valued as European, there is no completely explicit exact solution for the values of American puts. We use a technique called randomization to value American puts and calls on dividend-paying stocks. This technique yields a new semiexplicit approximation for American option values in the Black-Scholes model. Numerical results indicate th...

The direct transcription method for solving optimal control problems involves the use of a discrete approximation to the original problem. This paper describes a technique for changing the discretization in order to improve the accuracy of the approximation. An integer programming technique is used to minimize the maximum error during the refinement iterations. The efficiency of the method is i...

In this work we extend the trajectory piece-wise linear (TPWL) approximation of large, non-linear and input-affine dynamical systems to non-linear systems with non-linear input operators. The new technique is called the trajectory piece-wise quasi-linear (TPWQ) approximation. We explain the motivation for this technique in light of previously reported under-performance of the TPWL method and sh...

The ability to leverage organizational expertise is a critical success factor in most forms of knowledge work. However, expertise is an exceedingly difficult resource to manage. The design of computer-based support for knowledge management requires extensive, costly and inefficient cycles of knowledge elicitation to generate a reasonable knowledge map. We propose an alternative approximation te...

In this survey, we give an overview of a technique used to design and analyze algorithms that provide approximate solutions to NP -hard problems in combinatorial optimization. Because of parallels with the primal-dual method commonly used in combinatorial optimization, we call it the primal-dual method for approximation algorithms. We show how this technique can be used to derive approximation ...

This study is concerned with a new adaptive impedance control strategy to compensate for unknown time-varying environment stiffness and position. The uncertainties are expressed by Function Approximation Technique (FAT), which allows the update laws to be derived easily using Lyapunov stability theory. Computer simulation results are presented to validate the effectiveness of the proposed strat...

Fuzzy rough set theory is a candidate framework for query refinement. Indeed, a thesaurus defines an approximation space in which the query, which is a set of terms, can be approximated from the upper and the lower side. The upper approximation turns out to be too flexible however, resulting in query explosion, while the lower approximation is too strict, resulting in the empty query. Therefore...

We present texture cache approximation as a method for using existing hardware on GPUs to eliminate costly global memory accesses. We develop a technique for using a GPU’s texture fetch units to generate approximate values, and argue that this technique is applicable to a wide variety of GPU kernels. Applying texture cache approximation to an image blur kernel on an NVIDIA 780GTX, we obtain a 1...