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20042023
most citedNonnegative Matrix Factorization and I-Divergence Alternating Minimization

70 citations · 153 across the 10 of their papers we have counts for

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8 papers · 1 filter

math.OC2023

Synchronous deautoconvolution algorithm for discrete-time positive signals via I-divergence approximation

Lorenzo Finesso, Peter Spreij

We pose the problem of the optimal approximation of a given nonnegative signal with the scalar autoconvolution of a nonnegative signal , where and …

math.OC2021★ 4 cited

The inverse problem of positive autoconvolution

Lorenzo Finesso, Peter Spreij

We pose the problem of approximating optimally a given nonnegative signal with the scalar autoconvolution of a nonnegative signal. The I-divergence is chosen as the optimality crit…

math.OC2018

Approximation of nonnegative systems by moving averages of fixed order

Lorenzo Finesso, Peter Spreij

We pose the approximation problem for scalar nonnegative input-output systems via impulse response convolutions of finite order, i.e. finite order moving averages, based on repeate…

math.OC2013★ 4 cited

Approximation of Nonnegative Systems by Finite Impulse Response Convolutions

Lorenzo Finesso, Peter Spreij

We pose the deterministic, nonparametric, approximation problem for scalar nonnegative input/output systems via finite impulse response convolutions, based on repeated observations…

math.OC2010

Two-step Nonnegative Matrix Factorization Algorithm for the Approximate Realization of Hidden Markov Models

L. Finesso, A. Grassi, P. Spreij

We propose a two-step algorithm for the construction of a Hidden Markov Model (HMM) of assigned size, i.e. cardinality of the state space of the underlying Markov chain, whose -…

math.OC2006★ 29 cited

Approximation of stationary processes by Hidden Markov Models

Lorenzo Finesso, Angela Grassi, Peter Spreij

We aim at the construction of a Hidden Markov Model (HMM) of assigned complexity (number of states of the underlying Markov chain) which best approximates, in Kullback-Leibler dive…