We present a framework of adaptive estimation and rejuvenation of software system performance in the presence of aging sources. The framework specifies that a degradation model not only describe an aging process but also enable the adaptation of model-based performance estimates to on-line measurements of data pertaining to the aging process. The adaptive estimation uses model-based a priori es...

A modified method for satellite attitude control system in presence of novel actuators is proposed in this paper. The attitude control system is composed of three fluidic momentum controller (FMC) actuators that are used to control Euler angles and their dynamics is considered in satellite attitude equations as well. L1 adaptive control is utilized for satellite three-axial ...

As demand for high quality transmission increases increase of spectrum efficiency and an improvement of error performance in wireless communication systems are important . One of the promising approaches to 4G is adaptive OFDM (AOFDM) . Fixed modulation systems uses only one type of modulation scheme (or order), so that either performance or capacity should be compromised Adaptive modulated sys...

MRI is one of the most powerful techniques to study the internal structure of the body. MRI image quality is affected by various noises. Noises in MRI are usually thermal and mainly due to the motion of charged particles in the coil. Noise in MRI images also cause a limitation in the study of visual images as well as computer analysis of the images. In this paper, first, it is proved that proba...

In this paper, we study the impact of low-quality node on the performance of incremental least mean square (ILMS) adaptive networks. Adaptive networks involve many nodes with adaptation and learning capabilities. Low-quality mode in the performance of a node in a practical sensor network is modeled by the observation of pure noise (its observation noise) that leads to an unreliable measurement....

A novel two step adaptive identification framework is proposed for sinusoidal signals to estimate the unknown offset, amplitude, frequency and phase, where only the output measurements are used. After representing the sinusoidal signal as a linearly parameterized form, several adaptive laws are developed. The proposed adaptive laws are driven by parameter estimation error information that is de...

In this paper, we show that a hierarchical Bayesian modelling approach to sequential learning leads to many interesting attributes such as regularisation and automatic relevance determination. We identify three inference levels within this hierarchy, namely model selection, parameter estimation and noise estimation. In environments where data arrives sequentially, techniques such as cross-valid...

The paper presents a new approach for the estimation of harmonic components of a power system using a linear adaptive neuron called Adaline. The learning parameters in the proposed neural estimation algorithm are adjusted to force the error between the actual and desired outputs to satisfy a stable difference error equation. The estimator tracks the Fourier coefficients of the signal data corru...

Time-delay estimation is widely used in sonar and radar applications. In order to estimate time delay accurately in variable signal to noise ratio(SNR), an improved algorithm of adaptive time delay estimation(TDE) based on fourth-order cumulants has been proposed in this paper. The single adaptive filter in the conventional model is separated into two adaptive subunits connected in cascade, one...

A further optimisation of adaptive subspace-based frequency estimation for multiple real valued sine waves is considered in this paper. Authors proposed in [10] a novel combination of strong adaptive covariance matrix update and optimised block processing for frequency values retrieval. The new optimised approach combines the projection approximation subspace tracking technique based on deflati...