photo

Mojtaba Nazari


Last seen: 2 months ago Active since 2020

Followers: 13   Following: 0

Message

Statistics

File Exchange

6 Files

RANK
N/A
of 300,321

REPUTATION
N/A

CONTRIBUTIONS
0 Questions
0 Answers

ANSWER ACCEPTANCE
0.00%

VOTES RECEIVED
0

RANK
3,772 of 20,913

REPUTATION
400

AVERAGE RATING
5.00

CONTRIBUTIONS
6 Files

DOWNLOADS
48

ALL TIME DOWNLOADS
3218

RANK

of 168,093

CONTRIBUTIONS
0 Problems
0 Solutions

SCORE
0

NUMBER OF BADGES
0

CONTRIBUTIONS
0 Posts

CONTRIBUTIONS
0 Public Channels

AVERAGE RATING

CONTRIBUTIONS
0 Highlights

AVERAGE NO. OF LIKES

  • 5-Star Galaxy Level 3
  • Personal Best Downloads Level 3
  • First Review
  • First Submission

View badges

Feeds

View by

Submitted


Multivariate Jump Plus AM-FM Mode Decomposition (MJMD)
A novel method for decomposing a multivariate signal into AM-FM oscillations and discontinuous (jump)

4 months ago | 6 downloads |

0.0 / 5

Submitted


Jump Plus AM-FM Mode Decomposition (JMD)
A novel method for decomposing a nonstationary signal into amplitude- and frequency-modulated (AM-FM) oscillations and discontin...

6 months ago | 8 downloads |

5.0 / 5
Thumbnail

Submitted


Successive Jump and Mode Decomposition (SJMD)
SJMD decomposes the univariate (or multivariate) signal into jumps and multiple oscillatory components.

6 months ago | 9 downloads |

0.0 / 5
Thumbnail

Submitted


Multiscale Dynamic Graph Signal Analysis Toolbox (MDGABox)
MDGABox is used for decomposing the dynamic graph signals into oscillatory components and their associated dynamic connectivity ...

1 year ago | 4 downloads |

5.0 / 5
Thumbnail

Submitted


Successive Variational Mode Decomposition (SVMD.m)
This code is the corrected version of the SVMD (Ver. 1.1.1) which is a powerful signal decomposition algorithm.

4 years ago | 20 downloads |

0.0 / 5

Submitted


Variational Mode Extraction (VME.m)
This is a modified code of VME method (Ver. 2) which is a useful decomposition algorithm to extract a specific mode from the sig...

5 years ago | 4 downloads |

5.0 / 5