Современные подходы к формированию сбытовой политики организации

Материалы XX Междунар. науч.-техн. конф. студентов, аспирантов и молодых ученых, Гомель, 23–24 апр. 2020 г

Проект участка механического цеха по обработке деталей поперечно-строгального станка модели 7Д36 с разработкой технологического процесса механической обработки детали рычаг 7Д36.20А.113 и сравнительным анализом современных 3D – технологий в машиностроении

Real-time blind reverberation time estimation is of interest in speech enhancement techniques such as e.g. dereverberation and microphone beamforming. Advances in this field have been made where the diffusive reverberation tail is modeled and the decay rate is estimated using a maximum-likelihood approach. Various methods for reducing the computational complexity have also been presented. This paper proposes a method for even further computational complexity reduction, by more than 60% in some cases, and it is shown through simulations that the results of the proposed method are very similar to that of the original.QC 20131219</p

Low-Complexity Algorithms for Echo Cancellation in Audio Conferencing Systems

Ever since the birth of the telephony system, the problem with echoes, arising from impedance mismatch in 2/4-wire hybrids, or acoustic echoes where a loudspeaker signal is picked up by a closely located microphone, has been ever present. The removal of these echoes is crucial in order to achieve an acceptable audio quality for conversation. Today, the perhaps most common way for echo removal is through cancellation, where an adaptive filter is used to produce an estimated replica of the echo which is then subtracted from the echo-infested signal. Echo cancellation in practice requires extensive control of the filter adaptation process in order to obtain as rapid convergence as possible while also achieving robustness towards disturbances. Moreover, despite the rapid advancement in the computational capabilities of modern digital signal processors there is a constant demand for low-complexity solutions that can be implemented using low power and low cost hardware. This thesis presents low-complexity solutions for echo cancellation related to both the actual filter adaptation process itself as well as for controlling the adaptation process in order to obtain a robust system. Extensive simulations and evaluations using real world recorded signals are used to demonstrate the performance of the proposed solutions

Low-Complexity Adaptive Filtering for Acoustic Echo Cancellation in Audio Conferencing Systems

With the globalization of the world’s economy, the demand for effortless, quick and efficient communication is increasing. Modern audio conferencing allows people at different locations to have a conversation as if they were sitting in the same room, without having to travel. This obviously saves time and money, and also lessens the environmental strain caused by travel. Most audio conferencing systems and hands-free systems in particular, suffer from electric and/or acoustic echoes. Electric echoes typically originate from 2-4 wire conversion in hybrid circuits in the telephone network, while acoustic echoes arise due to acoustic coupling between loudspeaker and microphone. In digital audio communication equipment, the echoes are usually removed through digital signal processing methods such as adaptive filtering. Since audio conferencing systems are consumer electronic products, the manufacturing cost is a key issue. In order to accomplish low manufacturing costs, the choice of a low cost digital signal processor (DSP) to perform the signal processing tasks is central. Further, due to the limited resources of low cost DSPs, there is an intrinsic demand for low complexity signal processing algorithms. This thesis presents low complexity algorithms for adaptive filtering in acoustic echo cancellation applications. Both the actual update of the adaptive filter and the update control to prevent divergence and so called howling, are considered. Computer simulations, as well as real time implementations in actual acoustic systems are used to verify the performance of the proposed algorithms

Low-Complexity Adaptive Filtering for Acoustic Echo Cancellation in Audio Conferencing Systems

With the globalization of the world’s economy, the demand for effortless, quick and efficient communication is increasing. Modern audio conferencing allows people at different locations to have a conversation as if they were sitting in the same room, without having to travel. This obviously saves time and money, and also lessens the environmental strain caused by travel. Most audio conferencing systems and hands-free systems in particular, suffer from electric and/or acoustic echoes. Electric echoes typically originate from 2-4 wire conversion in hybrid circuits in the telephone network, while acoustic echoes arise due to acoustic coupling between loudspeaker and microphone. In digital audio communication equipment, the echoes are usually removed through digital signal processing methods such as adaptive filtering. Since audio conferencing systems are consumer electronic products, the manufacturing cost is a key issue. In order to accomplish low manufacturing costs, the choice of a low cost digital signal processor (DSP) to perform the signal processing tasks is central. Further, due to the limited resources of low cost DSPs, there is an intrinsic demand for low complexity signal processing algorithms. This thesis presents low complexity algorithms for adaptive filtering in acoustic echo cancellation applications. Both the actual update of the adaptive filter and the update control to prevent divergence and so called howling, are considered. Computer simulations, as well as real time implementations in actual acoustic systems are used to verify the performance of the proposed algorithms

Noise robust integration for blind and non-blind reverberation time estimation

The estimation of the decay rate of a signal section is an integral component of both blind and non-blind reverberation time estimation methods. Several decay rate estimators have previously been proposed, based on, e.g., linear regression and maximum-likelihood estimation. Unfortunately, most approaches are sensitive to background noise, and/or are fairly demanding in terms of computational complexity. This paper presents a low complexity decay rate estimator, robust to stationary noise, for reverberation time estimation. Simulations using artificial signals, and experiments with speech in ventilation noise, demonstrate the performance and noise robustness of the proposed method.QC 20160216</p