This paper uses univariate and multivariate singular spectrum analysis for predicting the value and the direction of changes in the daily pound / dollar exchange rate. To perform the forecast, we also use the daily dollar exchange rates with respect to Euro and Japanese yen. We use the random walk model as a benchmark model to evaluate performances of the singular spectrum analysis as a predict...

Gait Recognition is a biometric application that aims to identify a person by analyzing his/her gait. It is based on the fact that people often feel that they can identify a familiar person from afar simply by recognizing the way the person walks. In this work, a qualitative approach based on Granular computing paradigm is proposed. This paradigm involves information granules, based on density ...

In a previous paper (Varadi et al.), random-lag singular spectrum analysis was introduced for finding oscillations in very noisy and long time series. This work presents a generalization of the technique to search for common oscillations in two or more time series.

Automatic analysis of bioacoustic signals is a fundamental tool to evaluate the vitality our planet. Frogs and bees, for instance, may act like biological sensors providing information about environmental changes. This task ecological monitoring includes many challenges, such as nonuniform signal length processing, degraded target due noise, scarcity labeled samples training machine learning sy...

Dynamic Mode Decomposition (DMD) with time delay embedding is used to predict dynamic patterns in univariate series. An important pattern that can be extracted using DMD the trend or global change a series which useful for producing reliable forecast. utilizes computationally effi cient singular value decomposition (SVD) produce low rank approximation of linear operator brings about Trend trans...