2011 8th International Conference on Information, Communications &Amp; Signal Processing 2011
DOI: 10.1109/icics.2011.6173127
|View full text |Cite
|
Sign up to set email alerts
|

Relationship between the Haar transform and the MRT

Abstract: The Haar transform is an important signal transform that converts real input to real output, and it has been applied in various tasks in signal and image processing. The M-dimensional Real Transform (MRT) is a recently developed transform, and it shares the real-to-real conversion property of the Haar transform. This paper attempts to study the relationships between these two transforms.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
5
0

Year Published

2013
2013
2021
2021

Publication Types

Select...
4
1

Relationship

1
4

Authors

Journals

citations
Cited by 5 publications
(5 citation statements)
references
References 2 publications
0
5
0
Order By: Relevance
“…This structure of the UMRT definition has a similar form as that of the Haar transforms [10]. Table 3 shows the mapping for N ¼ 8.…”
Section: General Formula For Any Even Nmentioning
confidence: 96%
See 3 more Smart Citations
“…This structure of the UMRT definition has a similar form as that of the Haar transforms [10]. Table 3 shows the mapping for N ¼ 8.…”
Section: General Formula For Any Even Nmentioning
confidence: 96%
“…From Eqs. (10) and (11) and the definition of MRT in Eq. (1), ðÞ solutions for n in the range 0, N À 1 ½ , and thus, there exist gk , N ðÞ elements in the positive set.…”
Section: Theorem 1: Periodicitymentioning
confidence: 99%
See 2 more Smart Citations
“…Haar matrix, which is useful for localized signal analysis [19], edge detection [20], OFDM, and filter design and electrocardiogram (ECG) analysis, has been generalized for Jacket-Haar matrix [21], whose entries are 0 and ±2 compared with entries of the original Haar matrix being 1, −1, and 0. Although the 2 -point Jacket-Haar matrices are successfully proposed in [21], there is still a problem on how to construct the arbitrary-length Jacket-Haar transform as the arbitrary-length Walsh-Jacket transform has already done with high efficiency [22].…”
Section: Introductionmentioning
confidence: 99%