Two-dimensional filter bank design for optimal reconstruction using limited subband information

1995 ◽  
Vol 4 (8) ◽  
pp. 1160-1165 ◽  
Author(s):  
A. Tirakis ◽  
A. Delopoulos ◽  
S. Kollias
Keyword(s):  
Filter Bank ◽  
Two Dimensional ◽  
Optimal Reconstruction

scholarly journals Flexible Filter Bank Multi-Carriers PON Based on Two-Dimensional Multiple Probabilistic Shaping Distribution

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 1793-1799 ◽  
Author(s):  
Lei Jiang ◽  
Bo Liu ◽  
Yaya Mao ◽  
Jianxin Ren ◽  
Xing Xu ◽  
...  
Keyword(s):  
Filter Bank ◽  
Two Dimensional

Theory and design of two-dimensional DFT modulated filter bank with arbitrary modulation and decimation matrices

2015 ◽  
Vol 44 ◽  
pp. 123-130 ◽  
Author(s):  
Jun-Zheng Jiang ◽  
Fang Zhou ◽  
Peng-Lang Shui ◽  
Shan Ouyang
Keyword(s):  
Filter Bank ◽  
Two Dimensional

scholarly journals Task 1A DCASE 2021: Acoustic Scene Classification with mismatch-devices using squeeze-excitation technique and low-complexity constraint

2021 ◽  
Author(s):  
Javier Naranjo-Alcazar ◽  
Sergi Perez-Castanos ◽  
Maximo Cobos ◽  
Francesc J. Ferri ◽  
Pedro Zuccarello
Keyword(s):  
Filter Bank ◽  
Low Complexity ◽  
Two Dimensional ◽  
Scene Classification ◽  
Dimensional Representation ◽  
Percentage Points ◽  
Machine Listening ◽  
Audio Clip ◽  
Audio Data ◽  
Excitation Techniques

Acoustic scene classification (ASC) is one of the most popular problems in the field of machine listening. The objective of this problem is to classify an audio clip into one of the predefined scenes using only the audio data. This problem has considerably progressed over the years in the different editions of DCASE. It usually has several subtasks that allow to tackle this problem with different approaches. The subtask presented in this report corresponds to a ASC problem that is constrained by the complexity of the model as well as having audio recorded from different devices, known as mismatch devices (real and simulated). The work presented in this report follows the research line carried out by the team in previous years. Specifically, a system based on two steps is proposed: a two-dimensional representation of the audio using the Gamamtone filter bank and a convolutional neural network using squeeze-excitation techniques. The presented system outperforms the baseline by about 17 percentage points.

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