We present a matrix theoretic derivation of the Kalman filter—motivated by the statistical technique of minimum variance estimation—in order to make its theoretical underpinnings accessible to a broader audience. Standard derivations of the filter utilize probabilistic arguments that are less familiar to the matrix analyst and computational mathematician.

An algorithm for solving large-scale nonlinear' programs with linear constraints is presented. The method combines efficient sparse-matrix techniques as in the revised simplex method with stable quasi-Newton methods for handling the nonlinearities. A general-purpose production code (MINOS) is described, along with computational experience on a wide variety of problems.

A new method is developed for the state estimation of linear discrete-time stochastic system in the presence of unknown disturbance. The obtained filter is optimal in the unbiased minimum variance sense. The necessary and sufficient conditions for the existence and the stability of the filter are given.

A new discontinuity adaptive depth upsampling method is proposed in order to obtain a high-resolution depth map. The proposed method adaptively employs both the local minimum filter and the joint bilateral filter according to the variance of the depth map. Thus, it can reduce the over-blurred depth regions along the depth discontinuities. The experimental results demonstrate the feasibility of ...

In this article, a new outlier-resistant mechanism is proposed to deal with the variance-constrained filtering problem for class of networked systems subject sensor resolution under round-robin protocol (RRP). Sensor resolution, which serves as an important index in determining measurement accuracy, taken into account addressed problem, and sensor-resolution-induced uncertainty tackled by using...

Space-filling designs are important in computer experiments, which critical for building a cheap surrogate model that adequately approximates an expensive code. Many design construction techniques the existing literature only applicable rectangular bounded space, but real world applications, input space can often be non-rectangular because of constraints on variables. One solution to generate c...

CDMA systems are interference limited and therefore efficient interference management is necessary to enhance the capacity of a CDMA system. In this paper; we consider combining two effective receiver based interjerence management strategies: multiuser detection (temporal filtering) and receiver beamfoming (spatial$ltering). We formulate and examine the performunee of several linear filter stru...

We introduce the value-and-criterion filter structure, a new framework for designing filters based on mathematical morphology. The value-and-criterion filter structure is more flexible than the morphological structure, because it allows linear and nonlinear operations other than just the minimum and maximum to be performed on the data. One particular value-and-criterion filter, the Mean of Leas...

This paper aims at obtaining performance limitations of state estimation in terms of variance minimization (minimum variance estimation and filtering) using information theory. Two new notions, negentropy rate and Gaussianity-whiteness measure (joint Shannon-Wiener entropy), are proposed to facilitate the analysis. Topics such as Gaussianing-whitening filter (the maximum Gaussianity-whiteness m...