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- Ivan Dokmanic, Reza Parhizkar, Andreas Walther, Yue M. Lu, Martin Vetterli
- Proceedings of the National Academy of Sciences…
- 2013

Imagine that you are blindfolded inside an unknown room. You snap your fingers and listen to the room's response. Can you hear the shape of the room? Some people can do it naturally, but can we design computer algorithms that hear rooms? We show how to compute the shape of a convex polyhedral room from its response to a known sound, recorded by a few… (More)

- Reza Parhizkar, Ivan Dokmanic, Martin Vetterli
- 2014 IEEE International Conference on Acoustics…
- 2014

We propose a novel method for single-channel microphone localization inside a known room. Unlike other approaches, we take advantage of the room reverberation, which enables us to use only a single fixed loudspeaker to localize the microphone. Our method uses an echo labeling approach that associates the echoes to the correct walls. Echo labeling leverages… (More)

We present preliminary results obtained using a time domain wave-based reconstruction algorithm for an ultrasound transmission tomography scanner with a circular geometry. While a comprehensive description of this type of algorithm has already been given elsewhere, 2 the focus of this work is on some practical issues arising with this approach. In fact,… (More)

- Mohammad Javad Taghizadeh, Reza Parhizkar, Philip N. Garner, Hervé Bourlard
- 2013 18th International Conference on Digital…
- 2013

This paper addresses the application of missing data recovery via matrix completion for audio sensor networks. We propose a method based on Euclidean distance matrix completion for ad-hoc microphone array location calibration. This method can calibrate a full network from partial connectivity information. The pairwise distances of microphones in close… (More)

- Ivan Dokmanic, Reza Parhizkar, Juri Ranieri, Martin Vetterli
- ArXiv
- 2015

Euclidean distance matrices (EDM) are matrices of squared distances between points. The definition is deceivingly simple: thanks to their many useful properties they have found applications in psychometrics, crystallography, machine learning, wireless sensor networks, acoustics, and more. Despite the usefulness of EDMs, they seem to be insufficiently known… (More)

- Ivan Dokmanic, Reza Parhizkar, Juri Ranieri, Martin Vetterli
- IEEE Signal Processing Magazine
- 2015

Euclidean distance matrices (EDMs) are matrices of the squared distances between points. The definition is deceivingly simple; thanks to their many useful properties, they have found applications in psychometrics, crystallography, machine learning, wireless sensor networks, acoustics, and more. Despite the usefulness of EDMs, they seem to be insufficiently… (More)

- Reza Parhizkar, Amin Karbasi, Sewoong Oh, Martin Vetterli
- IEEE Transactions on Signal Processing
- 2013

We study the application of matrix completion in the process of calibrating physical devices. In particular we propose an algorithm together with reconstruction bounds for calibrating circular ultrasound tomography devices. We use the time-of-flight (ToF) measurements between sensor pairs in a homogeneous medium to calibrate the system. The calibration… (More)

- Mohammad Javad Taghizadeh, Reza Parhizkar, Philip N. Garner, Hervé Bourlard, Afsaneh Asaei
- Signal Processing
- 2015

This paper addresses the problem of ad hoc microphone array calibration where only partial information about the distances between microphones is available. We construct a matrix consisting of the pairwise distances and propose to estimate the missing entries based on a novel Euclidean distance matrix completion algorithm by alternative low-rank matrix… (More)

Euclidean distance matrices (EDM) are matrices of squared distances between points. The definition is deceivingly simple: thanks to their many useful properties they have found applications in psychometrics, crystallography, machine learning, wireless sensor networks, acoustics, and more. Despite the usefulness of EDMs, they seem to be insufficiently known… (More)

- Reza Parhizkar, Amin Karbasi, Martin Vetterli
- 2011 IEEE International Conference on Acoustics…
- 2011

We consider the position calibration problem in circular tomography devices, where sensors deviate from a perfect circle. We introduce a new method of calibration based on the time-of-flight measurements between sensors when the enclosed medium is homogeneous. Bounds on the reconstruction errors are proven and results of simulations mimicking a scanning… (More)