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M. Roughan

35 papers hereh-index 419.8k citations210 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author3
  • first author3
  • middle author14
  • last author15

Across the 35 of 35 papers where every author was matched, so the position is known.

fields
  • cs.SI6
  • cs.CR4
  • cs.IT4
  • cs.DB3
  • physics.soc-ph3
  • cs.DS2
same name
  • M. Roughan — 1 paper, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20132025
most citedClear as MUD: Generating, Validating and Applying IoT Behaviorial Profiles (Technical Report)

103 citations · 250 across the 29 of their papers we have counts for

collaborators
Showing cs.ITShow all

4 papers · 1 filter

cs.IT2022

The entropy rate of Linear Additive Markov Processes

Bridget Smart, Matthew Roughan, Lewis Mitchell

This work derives a theoretical value for the entropy of a Linear Additive Markov Process (LAMP), an expressive model able to generate sequences with a given autocorrelation struct…

cs.IT2021★ 1 cited

NPD Entropy: A Non-Parametric Differential Entropy Rate Estimator

Andrew Feutrill, Matthew Roughan

The estimation of entropy rates for stationary discrete-valued stochastic processes is a well studied problem in information theory. However, estimating the entropy rate for statio…

cs.IT2021★ 4 cited

Differential Entropy Rate Characterisations of Long Range Dependent Processes

Andrew Feutrill, Matthew Roughan

A quantity of interest to characterise continuous-valued stochastic processes is the differential entropy rate. The rate of convergence of many properties of LRD processes is slowe…

cs.IT2013

Hidden Markov Model Identifiability via Tensors

Paul Tune, Hung X. Nguyen, Matthew Roughan

The prevalence of hidden Markov models (HMMs) in various applications of statistical signal processing and communications is a testament to the power and flexibility of the model.…

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