Experiments on optimization of active control on a three‐dimensional acoustic source

1989 ◽  
Vol 85 (S1) ◽  
pp. S73-S73
Author(s):  
Jeffrey A. Giordano ◽  
Kenneth A. Cunefare ◽  
Gary Koopmann
Keyword(s):  
Active Control ◽  
Three Dimensional ◽  
Acoustic Source

scholarly journals Nonlinear active control of a cancerous tumour

2018 ◽  
Vol 7 (2.21) ◽  
pp. 72 ◽  
Author(s):  
Bhabani Shankar Dey ◽  
Manas Kumar Bera ◽  
Binoy Krishna Roy
Keyword(s):  
Active Control ◽  
Immune Cells ◽  
Normal Cell ◽  
Tumour Growth ◽  
Three Dimensional ◽  
Tumour Cells ◽  
Host Cells ◽  
Cancer Model ◽  
Control Objective ◽  
Simulation Results

This paper deals with the control of a cancerous tumour growth. The model used is a Three-Dimensional Cancer Model (TDCM). The competition terms include tumour cells, healthy cells, and immune cells. Nature of the competition among the populations of tumour cells, healthy host cells, and immune cells results in a chaotic behaviour. In this paper, a nonlinear active control has been used to control the growth of a tumour. Effect of chemotherapy drug on the different cell populations has been studied. Our control objective is to control the tumour growth and minimize its population to a small value which can be considered as harmless.Along with the above objective, the normal cell population is also be maintained at a particular level. This work has been done completely inin-sillico environment. The simulation results are shown extensively to support the theoretical analysis and confirmed that the preliminary objectives of the paper are attained.  

scholarly journals Synchronization and Electronic Circuit Application of Hidden Hyperchaos in a Four-Dimensional Self-Exciting Homopolar Disc Dynamo without Equilibria

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Yu Feng ◽  
Zhouchao Wei ◽  
Uğur Erkin Kocamaz ◽  
Akif Akgül ◽  
Irene Moroz
Keyword(s):  
Sliding Mode Control ◽  
Active Control ◽  
Electronic Circuit ◽  
Sliding Mode ◽  
Control Variable ◽  
Three Dimensional ◽  
Hyperchaotic System ◽  
Synchronization Errors ◽  
Mode Control ◽  
Additional Control

We introduce and investigate a four-dimensional hidden hyperchaotic system without equilibria, which is obtained by augmenting the three-dimensional self-exciting homopolar disc dynamo due to Moffatt with an additional control variable. Synchronization of two such coupled disc dynamo models is investigated by active control and sliding mode control methods. Numerical integrations show that sliding mode control provides a better synchronization in time but causes chattering. The solution is obtained by switching to active control when the synchronization errors become very small. In addition, the electronic circuit of the four-dimensional hyperchaotic system has been realized in ORCAD-PSpice and on the oscilloscope by amplitude values, verifying the results from the numerical experiments.

scholarly journals Towards End-to-End Acoustic Localization Using Deep Learning: From Audio Signals to Source Position Coordinates

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3418 ◽  
Author(s):  
Juan Vera-Diaz ◽  
Daniel Pizarro ◽  
Javier Macias-Guarasa
Keyword(s):  
Three Dimensional ◽  
Synthetic Data ◽  
Audio Signal ◽  
Real Data ◽  
Audio Signals ◽  
Acoustic Source ◽  
Acoustic Localization ◽  
Training Strategy ◽  
Audio Features ◽  
Novel Approach

This paper presents a novel approach for indoor acoustic source localization using microphone arrays, based on a Convolutional Neural Network (CNN). In the proposed solution, the CNN is designed to directly estimate the three-dimensional position of a single acoustic source using the raw audio signal as the input information and avoiding the use of hand-crafted audio features. Given the limited amount of available localization data, we propose, in this paper, a training strategy based on two steps. We first train our network using semi-synthetic data generated from close talk speech recordings. We simulate the time delays and distortion suffered in the signal that propagate from the source to the array of microphones. We then fine tune this network using a small amount of real data. Our experimental results, evaluated on a publicly available dataset recorded in a real room, show that this approach is able to produce networks that significantly improve existing localization methods based on SRP-PHAT strategies and also those presented in very recent proposals based on Convolutional Recurrent Neural Networks (CRNN). In addition, our experiments show that the performance of our CNN method does not show a relevant dependency on the speaker’s gender, nor on the size of the signal window being used.

Sign in / Sign up

Export Citation Format

Share Document