this paper presents a new control scheme for a class of nonlinear systems. in the proposed method, an adaptive neural network observer with rise feedback controller are applied to realize sensorless control scheme. this observer is tuned online and no exact information of nonlinear term of plant is required. so, this characteristic can compensate mismodeling phenomena. also, a new controller ca...

in some mobile systems, intelligent antennas are used to increase efficiency in a wide frequency band and different environmental and electromagnetic conditions. environmental factors, such as position of nearby objects, antenna mobility and even user type, can vary the antenna input impedance appreciably. therefore, it is necessary to incorporate an adaptive impedance matching circuit between ...

The minority game is relevant to current large scale information systems (such as the internet) as a model of the distributed nature of decision making in situations where agents must compete for a finite resource, e.g., bandwidth. This thesis reviews the minority game and discusses a “socially” optimal adaptive solution using a adaptive mixed strategy (i.e., stochastic) approach and a partial ...

This article proposes a method improving Kong et al. algorithm called Locally Adaptive Soft-Voting (LASV) algorithm described in ”General road detection from a single image”. This algorithm aims to detect and segment road in structured and unstructured environments. Evaluation of our method over different images datasets shows that it is speeded up by up to 32 times and precision is improved by...

Local adaptive image de-noising in transform domain is a powerfull tool for adapting to unknown smoothness of the images. In this work we propose to perform local adaptive denoising with adaptively varying local transform support size rather than using a transform with ¿xed size. We use a special rule (Intersection of Con¿dence Intervals ICI) to select the optimum window sizes locally. The algo...

By selectively zooming in and zooming out visualizations, the fisheye technique allows users to study details while maintaining context. In this paper, we introduce a multifisheye technique, which amounts to introducing several fisheyes in a visualization at the same time. Our multi-fisheye technique is based on partitioning the visualization’s display area and applying a fisheye algorithm insi...

An adaptive wavelet-based method is proposed for solving TV(total variation)–Allen–Cahn type models for multi-phase image segmentation. The adaptive algorithm integrates (i) grid adaptation based on a threshold of the sparse wavelet representation of the locally-structured solution; and (ii) effective finite difference on irregular stencils. The compactly supported interpolating-type wavelets e...

In this work, a hierarchical ensemble of projected clustering algorithm for high-dimensional data is proposed. The basic concept of the algorithm is based on the active learning method (ALM) which is a fuzzy learning scheme, inspired by some behavioral features of human brain functionality. High-dimensional unsupervised active learning method (HUALM) is a clustering algorithm which blurs the da...

Functional Magnetic Resonance Imaging inherently involves noisy measurements and a severe multiple test problem. Smoothing is usually used to reduce the effective number of multiple comparisons and to locally integrate the signal and hence increase the signal-to-noise ratio. Here, we provide a new structural adaptive segmentation algorithm (AS) that naturally combines the signal detection with ...