Fourier could be a data scientist: From graph Fourier transform to signal processing on graphs

The legacy of Joseph Fourier in science is vast, especially thanks to the essential tool that the Fourier transform is. The flexibility of this analysis, its computational efficiency and the physical interpretation it offers makes it a cornerstone in many scientific domains. With the explosion of digital data, both in quantity and diversity, the generalization of the tools based on Fourier transform is mandatory. In data science, new problems arose for the processing of irregular data such as social networks, biological networks or other data on networks. Graph signal processing is a promising approach to deal with those. The present text is an overview of the state of the art in graph signal processing, focusing on how to define a Fourier transform for data on graphs, how to interpret it and how to use it to process such data. It closes showing some examples of use. Along the way, the review reveals how Fourier's work remains modern and universal, and how his concepts, coming from physics and blended with mathematics, computer science, and signal processing, play a key role in answering the modern challenges in data science.     

A direct method for the solution of evolution problemsLa méthode directe

An alternative numerical method to solve structural evolution problems is presented. It belongs to the family of Large Time Increment Methods. The problem is solved on the whole time interval separating a global stage where a SA and KA solution is searched and a local stage where the constitutive law is satisfied. To solve the global stage, consuming the most CPU time, the mechanical fields are decomposed in a wavelet basis and the equilibrium is solved only for the largest coefficients. To cite this article: F. Comte et al., C. R. Mecanique 334 (2006).     

Wavelet modulation: An alternative modulation with low energy consumption

This paper presents wavelet modulation, based on the discrete wavelet transform, as an alternative modulation with low energy consumption. The transmitted signal has low envelope variations, which induces a good efficiency for the power amplifier. Wavelet modulation is analyzed and compared for different wavelet families with orthogonal frequency division multiplexing (OFDM) in terms of peak-to-average power ratio (PAPR), power spectral density (PSD) properties, and the impact of the power amplifier on the spectral regrowth. The performance in terms of bit error rate and complexity of implementation are also evaluated, and several trade-offs are characterized.