Publications related to Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

Demonstration of optical multicasting using Kerr frequency comb lines

Tobias Kippenberg, Maxim Karpov, Martin Hubert Peter Pfeiffer, Arne Kordts, Yan Yan, Zhe Zhao, Long Li, Lin Zhang, Amirhossein Mohajerin Ariaei

We experimentally demonstrate optical multicasting using Kerr frequency combs generated from a Si3N4 microresonator. We obtain Kerr combs in two states with different noise properties by varying the pump wavelength in the resonator and investigate the effe ...

Optical Society of America2016

Computing the Impact of White and Flicker Noise in Continuous-Time Integrator-Based ADCs

Maher Kayal, Adil Koukab, Paul Stanislas Gosselin

From first-order incremental Sigma Delta converters to controlled-oscillator-based converters, many ADC architectures are based on the continuous-time integration of the input signal. However, the accuracy of such converters cannot be properly estimated wi ...

Ieee2016

Simultaneous estimation of phase and its pth order derivatives

Pramod Rastogi, Rishikesh Dilip Kulkarni

One unaddressed challenge in optical metrology has been the measurement of higher order derivatives of rough specimens subjected to loading. In this paper, we investigate an approach that allows for the simultaneous estimation of the phase and its higher o ...

2016

Estimation of Phase and Its Higher Order Derivatives from a Single Complex Interferogram

Pramod Rastogi, Rishikesh Dilip Kulkarni

This paper reports a method for the simultaneous estimation of unwrapped phase and higher order phase derivatives from a single phase fringe pattern recorded in an optical interferometric setup, thereby overcoming substantial barriers to achieving such mea ...

2016

The recursive Hessian sketch for adaptive filtering

Martin Vetterli, Robin Scheibler

We introduce in this paper the recursive Hessian sketch, a new adaptive filtering algorithm based on sketching the same exponentially weighted least squares problem solved by the recursive least squares algorithm. The algorithm maintains a number of sketch ...

Ieee2016

MATHICSE Technical Report : Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

Fabio Nobile, Giovanni Migliorati

We study the accuracy of the discrete least-squares approximation on a finite dimensional space of a real-valued target function from noisy pointwise evaluations at independent random points distributed according to a given sampling probability measure. Th ...

MATHICSE2015

Noise analysis of genome-scale protein synthesis using a discrete computational model of translation

Vassily Hatzimanikatis, Julien Racle, Adam Stefaniuk

Noise in genetic networks has been the subject of extensive experimental and computational studies. However, very few of these studies have considered noise properties using mechanistic models that account for the discrete movement of ribosomes and RNA pol ...

Amer Inst Physics2015

Adaptive polynomial approximation by means of random discrete least squares

Giovanni Migliorati

We address adaptive multivariate polynomial approximation by means of the discrete least-squares method with random evaluations, to approximate in the L2 probability sense a smooth function depending on a random variable distributed according to a given pr ...

Springer2015

MATHICSE Technical Report : Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Fabio Nobile, Giovanni Migliorati

We analyze the accuracy of the discrete least-squares approximation of a function u in multivariate polynomial spaces

P_\Lambda := span\{y \mapsto y^\nu | \nu \in \Lambda\}

with

\Lambda\subset N_0^d

over the domain

\Gamma := [-1,1]^d

, based on the sa ...

MATHICSE2015

A noise reduction circuit technique for CMOS terahertz imaging

Christian Enz, Assim Boukhayma

This paper presents a noise reduction technique for Terahertz imaging based on modulating the THz source in order to transpose the signal at the output of the rectifier at a higher frequency where there is no 1/f noise and then filtering with a high Q band ...

IEEE2015

Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

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Demonstration of optical multicasting using Kerr frequency comb lines

Computing the Impact of White and Flicker Noise in Continuous-Time Integrator-Based ADCs

Simultaneous estimation of phase and its pth order derivatives

Estimation of Phase and Its Higher Order Derivatives from a Single Complex Interferogram

The recursive Hessian sketch for adaptive filtering

MATHICSE Technical Report : Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

Noise analysis of genome-scale protein synthesis using a discrete computational model of translation

Adaptive polynomial approximation by means of random discrete least squares

MATHICSE Technical Report : Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

A noise reduction circuit technique for CMOS terahertz imaging

Demonstration of optical multicasting using Kerr frequency comb lines

Simultaneous estimation of phase and its pth order derivatives

Estimation of Phase and Its Higher Order Derivatives from a Single Complex Interferogram

Computing the Impact of White and Flicker Noise in Continuous-Time Integrator-Based ADCs

Adaptive polynomial approximation by means of random discrete least squares

The recursive Hessian sketch for adaptive filtering

Noise analysis of genome-scale protein synthesis using a discrete computational model of translation

MATHICSE Technical Report : Convergence estimates in probability and in expectation for discrete least squares with noisy evaluations at random points

A noise reduction circuit technique for CMOS terahertz imaging

MATHICSE Technical Report : Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension