11 accepted papers
Random data sketching (or projection) is now a classical technique enabling, for instance, approximate numerical linear algebra and machine learning algorithms with reduced computational complexity and memory. In this context, the possibility of performing data processing (such as pattern detection…
We propose a numerical interferometry method for identification of optical multiply-scattering systems when only intensity can be measured. Our method simplifies the calibration of optical transmission matrices from a quadratic to a linear inverse problem by first recovering the phase of the measure…
Approximating kernel functions with random features (RFs) has been a successful application of random projections for nonparametric estimation. However, performing random projections presents computational challenges for large-scale problems. Recently, a new optical hardware called Optical Processin…
In this paper we tackle the problem of recovering the phase of complex linear measurements when only magnitude information is available and we control the input. We are motivated by the recent development of dedicated optics-based hardware for rapid random projections which leverages the propagation…
This study proposes a principled method to jointly determine the placement of acoustic sources (loudspeakers) and sensors (control points/microphones) in sound field control. The goal of this setup is to efficiently produce a sound field using multiple loudspeakers, approximately matching a target s…
This study is an experimental validation of a new closed-form method for automatic array position calibration, based on time of arrival (TOA) measurements between sources and sensors. An experiment with a large array composed of 121 microphones and a dozen of sources has been set up. We first show t…
Recent works on reconstruction of room geometry from echoes assume that the geometry of the sensor array is known. In this paper, we show that such an assumption is not essential; echoes provide sufficient clues to reconstruct the room's and the array's geometries jointly, even from a single acousti…
In this paper, the problem of compressive imaging is addressed using natural randomization by means of a multiply scattering medium. To utilize the medium in this way, its corresponding transmission matrix must be estimated. For calibration purposes, we use a digital micromirror device (DMD) as a si…
This paper investigates the problem of estimating the shape or the boundary impedance of a vibrating membrane from acoustic measurements in a limited sub-domain of the membrane. In acoustics, polygonal room shapes are usually estimated through room impulse response measurements. Impedance values of…
Random projections have proven extremely useful in many signal processing and machine learning applications. However, they often require either to store a very large random matrix, or to use a different, structured matrix to reduce the computational and memory costs. Here, we overcome this difficult…
We study the problem of microphone array localization in a strongly reverberant room, where time of arrivals (TOA) or time difference of arrivals (TDOA) cannot always be measured precisely. Instead, we use frequency-domain measurements to calibrate the array position, based on the modes of the room,…