Publications by Reza Parhizkar

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Euclidean distance matrices (EDMs) are central players in many diverse fields including psychometrics, NMR spectroscopy, machine learning and sensor networks. However, they are not often exploited in signal processing. In this thesis, we analyze attributes ...

A central problem in signal processing and communications is to design signals that are compact both in time and frequency. Heisenberg's uncertainty principle states that a given function cannot be arbitrarily compact both in time and frequency, defining a ...

For a given time or frequency spread, one can always find continuous- time signals, which achieve the Heisenberg uncertainty principle bound. This is known, however, not to be the case for discrete-time sequences; only widely spread sequences asymptoticall ...

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, wireles ...

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 e ...

This paper addresses the problem of ad hoc microphone array calibration where only partial information about the distances between the microphones is available. We construct a matrix consisting of the pairwise distances and propose to estimate the missing ...

We study the calibration process in circular ultrasound tomography devices where the sensor positions deviate from the circumference of a perfect circle. This problem arises in a variety of applications in signal processing ranging from breast imaging to s ...

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 homogene ...

An indoor localization method for estimating the location of nodes (n1, n2), at least one node (n1) being connected to at least another node (n2) by at least two different channels (ch1, ch1′), comprising the following steps: measuring a distance between t ...

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 com ...

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 u ...

Reza Parhizkar

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Euclidean Distance Matrices : Properties, Algorithms and Applications

Sequences with Minimal Time-Frequency Uncertainty

Sequences with Minimal Time-Frequency Spreads

Euclidean Distance Matrices: Essential Theory, Algorithms and Applications

Sound Speed Estimation Using Wave-based Ultrasound Tomography: Theory and GPU Implementation

Ad Hoc Microphone Array Calibration: Euclidean Distance Matrix Completion Algorithm and Theoretical Guarantees

Calibration Using Matrix Completion with Application to Ultrasound Tomography

Calibration in Circular Ultrasound Tomography Devices

Indoor localization method and system

Acoustic Echoes Reveal Room Shape

Single-Channel Indoor Microphone Localization