activity
20182021
most citedA Multi-Target Track-Before-Detect Particle Filter Using Superpositional Data in Non-Gaussian Noise

38 citations · 39 across the 2 of their papers we have counts for

collaborators

5 papers

cs.SD20211 cited

A Joint Diagonalization Based Efficient Approach to Underdetermined Blind Audio Source Separation Using the Multichannel Wiener Filter

Nobutaka Ito, Rintaro Ikeshita, Hiroshi Sawada +1

This paper presents a computationally efficient approach to blind source separation (BSS) of audio signals, applicable even when there are more sources than microphones (i.e., the…

eess.SP202038 cited

A Multi-Target Track-Before-Detect Particle Filter Using Superpositional Data in Non-Gaussian Noise

Nobutaka Ito, Simon Godsill

This paper proposes a novel particle filter for tracking time-varying states of multiple targets jointly from superpositional data, which depend on the sum of contributions of all…

cs.SD2018

FastFCA-AS: Joint Diagonalization Based Acceleration of Full-Rank Spatial Covariance Analysis for Separating Any Number of Sources

Nobutaka Ito, Tomohiro Nakatani

Here we propose FastFCA-AS, an accelerated algorithm for Full-rank spatial Covariance Analysis (FCA), which is a robust audio source separation method proposed by Duong et al. ["Un…

cs.SD2018

FastFCA: A Joint Diagonalization Based Fast Algorithm for Audio Source Separation Using A Full-Rank Spatial Covariance Model

Nobutaka Ito, Shoko Araki, Tomohiro Nakatani

A source separation method using a full-rank spatial covariance model has been proposed by Duong et al. ["Under-determined Reverberant Audio Source Separation Using a Full-rank Spa…

eess.AS2018

The 2018 Signal Separation Evaluation Campaign

Fabian-Robert Stöter, Antoine Liutkus, Nobutaka Ito

This paper reports the organization and results for the 2018 community-based Signal Separation Evaluation Campaign (SiSEC 2018). This year's edition was focused on audio and pursue…