A general form of the timefrequency distribution with complex-lag argument is proposed. It is based on the Generalized complex-lag distribution, modified to provide an efficient instantaneous frequency estimation in the case of multicomponent signals. The form of proposed distribution is suitable for numerical realization and it provides an arbitrarily high distribution concentration. The theory is illustrated by an example.

Independent living of older adults is one of the main challenges linked to the ageing population. Especially those living with diseases like COPD, MCI or frailty, need more Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation support in everyday life and this is by itself a big societal challenge with impact in multiple sectors. In this paper we present eWALL, an innovative open-source eHealth platform that aims to address these challenges by means of an advanced cloud-based infrastructure. eWALL is designed in an innovative manner and achieved technical breakthroughs in eHealth platforms, while prioritizing user and market needs that are often abandoned and are the major reason for technically sound solutions that fail. We consider this as an opportunity and we aim to change the eHealth systems' experience for older adults and break the barriers for the penetration of ICT solutions.

An approach to speech watermarking based on the time-frequency signal analysis is proposed. As a time-frequency representation suitable for speech analysis, the S-method is used. The time-frequency characteristics of watermark are modeled by using speech components in the selected region. The modeling procedure is based on the concept of time-varying filtering. A detector form that includes cross-terms in the Wigner distribution is proposed. Theoretical considerations are illustrated by the examples. Efficiency of the proposed procedure has been tested for several signals and under various attacks.

A watermarking approach based on multidimensional time-frequency analysis is proposed. It represents a unified concept that can be used for different types of data such as audio, speech signals, images or video. Time-frequency analysis is employed for speech signals, while space/spatial-frequency analysis is used for images. Their combination is applied for video signals. Particularly, we focus on the 2-D case: space/spatial-frequency based image watermarking procedure that will be subsequently extended to video signal. A method that selects coefficients for watermarking by estimating the local frequency content is proposed. In order to provide watermark imperceptibility, the nonstationary filtering is used to model the watermark which corresponds to the host signal components. Furthermore, the watermark detection within the multidimensional time-frequency domain is proposed. The efficiency and robustness of the procedure in the presence of various attacks is proven experimentally.

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