In this paper we propose a novel training algorithm for RBF networks that is based on extended kalman filter and fuzzy logic.After the user choose how many prototypes to include in the network, the extended kalman filter simultancously solves for the prototype vectors and the weight matrix.The fuzzy logic is used to cope with the devergence problem caused by the insufficiently known a priori fi...

We propose a novel coplanar filter, which exploits the coplanarity of gray-level distribution of neighboring pixels, to pre-filter the document images. Experiments show that the proposed filter exhibits the following desired properties for document image binarization: (1) impulsive noise removal, (2) piecewise smoothing, and (3) sharp edge preservation.

This paper optimizes a GPS smoothing filter to minimize biases caused by ionosphere divergence during anomalous storms. Ionospheric storms represent the most severe threat to high-integrity differential GPS systems, such as Ground-Based Augmentation Systems (GBAS). Substituting the optimized filter for the Hatch Filter typically used in GBAS reduces ionosphere divergence bias by over 10% for a ...

Mrstract—The notion is exploded that to build a Kalman–Bucy filter, one needs to know tbe whole structure of the signal generating process. It is shown that the filter is constructible knowing precisely those covariwrces required to construct a Wiener filter, and no more, and that the filter is independent of the particular models of the processes generating these covariances. Performance of th...

We propose a novel coplanar filter, which exploits the coplanarity of gray-level distribution of neighboring pixels, to pre-filter the document images. Experiments show that the proposed filter exhibits the following desired properties for document image binarization: (1) impulsive noise removal, (2) piecewise smoothing, and (3) sharp edge preservation.

This paper presents a new robust fault and state estimation based on recursive least square filter for linear stochastic systems with unknown disturbances. The novel elements of the algorithm are : a simple, easily implementable, square root method which is shown to solve the numerical problems affecting the unknown input filter algorithm and related information filter and smoothing algorithms;...

In this paper, we present a spatially adaptive method to reduce compression artifacts observed in block discrete cosine transform (DCT) based image/video compression standards. The method is based on the bilateral filter, which is very effective in denoising images without smoothing edges. When applied to reduce compression artifacts, the parameters of the bilateral filter should be chosen care...

We propose a novel coplanar filter, which exploits the coplanarity of gray-level distribution of neighboring pixels, to pre-filter the document images. Experiments show that the proposed filter exhibits the following desired properties for document image binarization: (1) impulsive noise removal, (2) piecewise smoothing, and (3) sharp edge preservation.

− In this paper a development of an adaptive Kalman filter through a fuzzy inference system (FIS) is outlined. The adaptation is concerned with the imposition of conditions under which the filter measurement noise covariance matrix R or the process noise covariance matrix Q are estimated. The adaptive adjustment is carried out using a FIS based on the whiteness of the filter innovation sequence...