Wyniki wyszukiwania - BazTech

1

Deep Learning-based Beamforming Approach Incorporating Linear Antenna Arrays

Bhalke Daulappa, Paikrao Pavan D., Anguera Jaume

Journal of Telecommunications and Information Technology

|

2024

|

nr 2

66--70

EN

This research delves into exploring machine learning and deep learning techniques relied upon in antenna design processes. First, the general concepts of machine learning and deep learning are introduced. Then, the focus shifts to various antenna applications, such as those relying on millimeter waves. The feasibility of employing antennas in this band is examined and compared with conventional methods, emphasizing the acceleration of the antenna design process, reduction in the number of simulations, and improved computational efficiency. The proposed method is a low-complexity approach which avoids the need for eigenvalue decomposition, the procedure for computing the entire matrix inversion, as well as incorporating signal and interference correlation matrices in the weight optimization process. The experimental results clearly demonstrate that the proposed method outperforms the compared beamformers by achieving a better signal-to-interference ratio.

2

Performance Analysis of MVDR Beamformer Applied on an End-fire Microphone Array Composed of Unidirectional Microphones

Šarić Zoran, Subotić Miško, Bilibajkić Ružica, Barjaktarović Marko, Zdravković Nebojša

Archives of Acoustics

|

2021

|

Vol. 46, No. 4

611--621

EN

Microphone array with minimum variance (MVDR) beamformer is a commonly used method for ambient noise suppression. Unfortunately, the performance of the MVDR beamformer is poor in a real reverberant room due to multipath wave propagation. To overcome this problem, we propose three improvements. Firstly, we propose end-fire microphone array that has been shown to have a better directivity index than the corresponding broadside microphone array. Secondly, we propose the use of unidirectional microphones instead of omnidirectional ones. Thirdly, we propose an adaptation of its adaptive algorithm during the pause of speech, which improves its robustness against the room reverberation and deviation from the optimal receiving direction. The performance of the proposed microphone array was theoretically analyzed using a diffuse noise model. Simulation analysis was performed for combined diffuse and coherent noise using the image model of the reverberant room. Real room tests were conducted using a four-microphone array placed in a small office room. The theoretical analysis and the real room tests showed that the proposed solution considerably improves speech quality.

3

Acoustic field distribution in speech with the use of the microphone array

Król D., Lorenc A.

Tarnowskie Colloquia Naukowe. Nauki Techniczne i Ścisłe

|

2017

|

T. 4, nr 3

9--16

EN

This article presents a 16-channel microphone-array recorder/processor that allows for a simultaneous and non-invasive detection of oral, oronasal and nasal segments in speech. Such devices and methods have not been used in the research on the articulation of sounds in the world’s languages. In this paper analysis of Polish nasal vowel was presented. Adaptive beamforming method used for rendering three-dimensional acoustic fields of the recorded audio data has been shown.

4

Implementation of Adaptive Generalized Sidelobe Cancellers Using Efficient Complex Valued Arithmetic

Glentis G. O.

International Journal of Applied Mathematics and Computer Science

|

2003

|

Vol. 13, no 4

549-566

EN

Low complexity realizations of Least Mean Squared (LMS) error, Generalized Sidelobe Cancellers (GSCs) applied to adaptive beamforming are considered. The GSC method provides a simple way for implementing adaptive Linear Constraint Minimum Variance (LCMV) beamformers. Low complexity realizations of adaptive GSCs are of great importance for the design of high sampling rate, and/or small size and low power adaptive beamforming systems. The LMS algorithm and its Transform Domain (TD-LMS) counterpart are considered for the adaptive processing task involved in the design of optimum GSC systems. Since all input signals are represented by complex variables, complex valued arithmetic is utilized for the realization of GSC algorithms, either on general purpose computers, or on dedicated VLSI ASICs. Using algorithmic strength reduction (SR) techniques, two novel algorithms are developed for efficient realizations of both LMS GSCs and TD-LMS GSC schemes. Both of the proposed algorithms are implemented using real valued arithmetic only, whilst reducing the number of multipliers by 25% and 20%, respectively. When VLSI implementation aspects are considered, both the proposed algorithms result in reduced power dissipation and silicon area realizations. The performance of the proposed realizations of the LMS based GSC methods is illustrated in the context of typical beamforming applications.