We present a “twice universal” linear prediction algorithm over the unknown parameters and model orders, in which the sequentially accumulated square prediction error is as good as any linear predictor of order up to some M , for any individual sequence. The extra loss comprises of a parameter “redundancy” term proportional to (p/2)n-’ In(h), and a model order “redundancy” term proportional to ...

In the context of hyperspectral image analysis in planetology, we show how to estimate the physical parameters that generate the spectral infrared signal reflected by Mars. The training approach we develop is based on the estimation of the functional relationship between parameters and spectra, using a database of synthetic spectra generated by a physical model. The high dimension of spectra is...

We investigate the convergence behavior of the normalized least mean square (NLMS) algorithm in the structure of a linear transversal filter. At the n-th iteration, the traditional NLMS transversal filter generates the n-th output signal by using linear convolution of the n-th input vector and the n-th coefficient vector. Based on this result, the n-th coefficient vector is updated to the n + 1...

The real-time performance of a fundamental frequency estimation algorithm depends not only on its computational eeciency but also on its ability to obtain accurate estimates from short signal segments. Previous frequency-domain algorithms make use of spectral analysis algorithms that require the application of a window function, which cause them to fail when signal segments are short and their ...

LPC analysis is one of the most powerful techniques in speech analysis. Spectral zeros during consonant or consonant-vowel transition regions introduce difficulties in estimating LPC parameters. In this paper, we propose to estimate formant frequencies from LPC model by MUSIC (Multiple Signal Classification) and ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques). Form...

Adaptive filter is an efficient method to filter ECG signal, because it does not need the signal statistical characteristics. In this paper we present a Gaussian & novel adaptive filter for removing the Baseline wander & power line interference from ECG signals based on recursive least mean square (RLMS) algorithm & Normalized least mean square (NLMS) algorithm. These algorithms are derived bas...