Review

classic mds function cmdscale (MathWorks Inc)

MathWorks Inc is a verified supplier

About

News

Press Release

Team

Advisors

Partners

Contact

Bioz Stars

Bioz vStars

Buy from Supplier

Structured Review

MathWorks Inc classic mds function cmdscale
Classic Mds Function Cmdscale, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/classic+mds+function+cmdscale/10__1016_slash_j__apacoust__2024__110023-150-18-17
Average 90 stars, based on 1 article reviews

classic mds function cmdscale - by Bioz Stars, 2026-10

90/100 stars

Images

other:

Article Title: Single-source zones detection using relative harmonic coefficients under diverse acoustic scenarios
Article Snippet: Applied Acoustics 221 (2024) 110023 Contents lists available at ScienceDirect Applied Acoustics journal homepage: www.elsevier.com/locate/apacoust Single-source zones detection using relative harmonic coefficients under diverse acoustic scenarios Yonggang Hu ∗, Hewen Wei, Xiaoxiang Zhu, Yang Guan Shanghai branch of the Southwest Institute of Electronics and Telecommunication Technology of China, Shanghai 200434, China A R T I C L E I N F O A B S T R A C T Keywords: Single-source zones detection Spherical harmonics domain Relative harmonic coefficients Diverse acoustic scenarios Accurate detection of single-source zones, where only a single source is active or dominant within the mixed recordings, benefits many acoustic signal processing techniques, while with very little research focusing on this topic.. This article uses a higher-order sensor array and proposes a spherical harmonics (SH) domain detector that is applicable under diverse acoustic scenarios.. The detector utilizes multi-dimensional scaling (MDS) by projecting a recently introduced SH-domain feature denoted relative harmonic coefficients (RHC) into a lowdimensional space, where the single-source zones can be easily recognized as they locate at distinctive positions compared to the overlapped and source-absent zones.

Image Search Results

Analysis of background functional connectivity reveals changes over the time course of epileptogenesis. A , E , I , Individual connectivity matrices represented as dots in the first two principal dimensions of the multidimensional scaling of Frobenius distances between the individual connectivity matrices. Each dot represents a single matrix (green, Day 0; yellow, Day 7; red, Day 28; gray, Sham control; empty symbols: circle, diamond, and square represent the median of the connectivity matrices). The first three principal multidimensional scaling dimensions represent ∼70% of the relations encoded in the raw Frobenius distances ( R 2 ABS =0.66, R 2 MAX =0.72, R 2 MIN =0.7; R is Pearson’s correlation coefficient between the Frobenius distances in the matrix space and the Euclidian distances in the reconstructed space); for clarity only the first two coordinates are plotted. B – D , F – H , J – L , Median functional connectivity matrices (indicated with empty symbols in A , E , I ) resulting from the three different measures at different days with color-coded connection weights (Day 0 over 11 matrices, Day 7 over 6 matrices, Day 28 over 8 matrices; different numbers of matrices for individual days because of quality of recordings; see Materials and Methods).

Journal: eNeuro

Article Title: Background EEG Connectivity Captures the Time-Course of Epileptogenesis in a Mouse Model of Epilepsy

doi: 10.1523/ENEURO.0059-19.2019

Figure Lengend Snippet: Analysis of background functional connectivity reveals changes over the time course of epileptogenesis. A , E , I , Individual connectivity matrices represented as dots in the first two principal dimensions of the multidimensional scaling of Frobenius distances between the individual connectivity matrices. Each dot represents a single matrix (green, Day 0; yellow, Day 7; red, Day 28; gray, Sham control; empty symbols: circle, diamond, and square represent the median of the connectivity matrices). The first three principal multidimensional scaling dimensions represent ∼70% of the relations encoded in the raw Frobenius distances ( R 2 ABS =0.66, R 2 MAX =0.72, R 2 MIN =0.7; R is Pearson’s correlation coefficient between the Frobenius distances in the matrix space and the Euclidian distances in the reconstructed space); for clarity only the first two coordinates are plotted. B – D , F – H , J – L , Median functional connectivity matrices (indicated with empty symbols in A , E , I ) resulting from the three different measures at different days with color-coded connection weights (Day 0 over 11 matrices, Day 7 over 6 matrices, Day 28 over 8 matrices; different numbers of matrices for individual days because of quality of recordings; see Materials and Methods).

Article Snippet: Next, we used classical multidimensional scaling (MDS) to visualize relations captured by the similarity matrix , using MATLAB (Release 2018b, MathWorks) function cmdscale.

Techniques: Functional Assay, Control