Adaptive filtering algorithms are pervasive throughout signal processing and have had a material impact on wide variety of domains including audio processing, telecommunications, biomedical sensing, astrophysics cosmology, seismology, many more. filters typically operate via specialized online, iterative optimization methods such as least-mean squares or recursive least aim to process signals i...

This study compares the effectiveness of various image enhancement filters for improving the perceived visibility of coloured digital natural images for people with visual impairment. Generic filters were compared with Peli's adaptive enhancement and adaptive thresholding and custom-devised filters based on each subject's contrast sensitivity loss. Subjects with low vision made within filter ra...

We consider adaptive periodic IIR ltering and present an extension of the Hyperstable Adaptive Recursive Filter (HARF). We give conditions for convergence of the parameter estimate error, involving passivity of certain operators in the identi cation loop, identi ability of the system parameters, and persistent excitation (pe). A necessary and su cient condition for identi ability is given and s...

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Adaptive Packet Filters (APFs) are motivated by the proliferation of distributed servers and the lack of Quality-of-Service (QoS) management solutions for them. APFs merge packet-filtering and server load monitoring into a novel load-sensitive packet-filtering abstraction for overload protection and QoS differentiation. They integrate well into network protocol stacks and firewalls, scale to la...

Several adaptive order statistic filters (OSF) are developed and compared for channel characterization and noise suppression in images and 3-D CT data. Emphasis has been put on the situation when a noise-free reference image is not available but instead we can have a sequence of two noisy versions of the same image (or a 3-D data slice). One of the noisy images is used as the reference in the O...

We introduce the adaptive cuckoo filter (ACF), a data structure for approximate set membership that extends cuckoo filters by reacting to false positives, removing them for future queries. As an example application, in packet processing queries may correspond to flow identifiers, so a search for an element is likely to be followed by repeated searches for that element. Removing false positives ...

In this paper we consider the problem of change detection and non stationary signals tracking. Using parametric estimation of signals based on least square lattice adaptive filters we consider for change detection statistical parametric methods using likelihood ratio and hypothesis tests. In order to track signals dynamics, we introduce a compensation procedure in the adaptive estimation. This ...

This paper is a tutorial survey which focuses on some developments introduction in statistical filtering achieved since the of Wiener and Kalman filters for linear gaussian problems. Kalman are reviewed with filters (including reference to their smoothers and predictors) interesting properties and also their fundamental limitations in nonlinear or unknown environments. For nonlinear filtering p...