Acoustic Echo Cancellation and their Application in ADF

In this paper, we present an overview of the principal, structure and the application of the echo cancellation and kind of application to improve the performance of the systems. Echo is a process in which a delayed and distorted version o the original sound or voice signal is reflected back to the source. For the acoustic echo canceller much and more study are required to make the good tracking speed fast and reduce the computational complexity. Due to the increasing the processing requirement, widespread implementation had to wait for advances in LSI, VLSI echo canceller appeared. DOI: 10.17762/ijritcc2321-8169.150513

The NLMS algorithm with time-variant optimum stepsize derived from a Bayesian network perspective

In this article, we derive a new stepsize adaptation for the normalized least mean square algorithm (NLMS) by describing the task of linear acoustic echo cancellation from a Bayesian network perspective. Similar to the well-known Kalman filter equations, we model the acoustic wave propagation from the loudspeaker to the microphone by a latent state vector and define a linear observation equation (to model the relation between the state vector and the observation) as well as a linear process equation (to model the temporal progress of the state vector). Based on additional assumptions on the statistics of the random variables in observation and process equation, we apply the expectation-maximization (EM) algorithm to derive an NLMS-like filter adaptation. By exploiting the conditional independence rules for Bayesian networks, we reveal that the resulting EM-NLMS algorithm has a stepsize update equivalent to the optimal-stepsize calculation proposed by Yamamoto and Kitayama in 1982, which has been adopted in many textbooks. As main difference, the instantaneous stepsize value is estimated in the M step of the EM algorithm (instead of being approximated by artificially extending the acoustic echo path). The EM-NLMS algorithm is experimentally verified for synthesized scenarios with both, white noise and male speech as input signal.Comment: 4 pages, 1 page of reference

A Practical Data-Reuse Adaptive Algorithm for Acoustic Echo Cancellation

Publication in the conference proceedings of EUSIPCO, Bucharest, Romania, 201

Robust adaptive filtering algorithms for system identification and array signal processing in non-Gaussian environment

This dissertation proposes four new algorithms based on fractionally lower order statistics for adaptive filtering in a non-Gaussian interference environment. One is the affine projection sign algorithm (APSA) based on L₁ norm minimization, which combines the ability of decorrelating colored input and suppressing divergence when an outlier occurs. The second one is the variable-step-size normalized sign algorithm (VSS-NSA), which adjusts its step size automatically by matching the L₁ norm of the a posteriori error to that of noise. The third one adopts the same variable-step-size scheme but extends L₁ minimization to Lp minimization and the variable step-size normalized fractionally lower-order moment (VSS-NFLOM) algorithms are generalized. Instead of variable step size, the variable order is another trial to facilitate adaptive algorithms where no a priori statistics are available, which leads to the variable-order least mean pth norm (VO-LMP) algorithm, as the fourth one. These algorithms are applied to system identification for impulsive interference suppression, echo cancelation, and noise reduction. They are also applied to a phased array radar system with space-time adaptive processing (beamforming) to combat heavy-tailed non-Gaussian clutters. The proposed algorithms are tested by extensive computer simulations. The results demonstrate significant performance improvements in terms of convergence rate, steady-state error, computational simplicity, and robustness against impulsive noise and interference --Abstract, page iv

A Novel Adaptive method for Acoustic Echo Cancellation

Speech is compulsory in audio teleconferenceing system. In present scenareo acoustic echo is a major setback for user and causes a lessening in the quality of the communication.By means of some adaptive filtering methods acoustic echo canbe eliminated and can be reachrd in a desired value. A detail performance assessment is reported, including echo return loss enhancement (ERLE), convergence time and system distance metrics.We have also compared two different signals and how noise can be cancelled out using NLMS algorithm

An FPGA architecture design of a high performance adaptive notch filter

The occurrence of narrowband interference near frequencies carrying information is a common problem in modern control and signal processing applications. A very narrow notch filter is required in order to remove the unwanted signal while not compromising the integrity of the carrier signal. In many practical situations, the interference may wander within a frequency band, in which case a wider notch filter would be needed to guarantee its removal, which may also allow for the degradation of information being carried in nearby frequencies. If the interference frequency could be autonomously tracked, a narrow bandwidth notch filter could be successfully implemented for the particular frequency. Adaptive signal processing is a powerful technique that can be used in the tracking and elimination of such a signal. An application where an adaptive notch filter becomes necessary is in biomedical instrumentation, such as the electrocardiogram recorder. The recordings can become useless when in the presence of electromagnetic fields generated by power lines. Research was conducted to fully characterize the interference. Research on notch filter structures and adaptive filter algorithms has been carried out. The lattice form filter structure was chosen for its inherent stability and performance benefits. A new adaptive filter algorithm was developed targeting a hardware implementation. The algorithm used techniques from several other algorithms that were found to be beneficial. This work developed the hardware implementation of a lattice form adaptive notch filter to be used for the removal of power line interference from electrocardiogram signals. The various design tradeo s encountered were documented. The final design was targeted toward multiple field programmable gate arrays using multiple optimization efforts. Those results were then compared. The adaptive notch filter was able to successfully track and remove the interfering signal. The lattice form structure utilized by the proposed filter was verified to exhibit an inherently stable realization. The filter was subjected to various environments that modeled the different power line disturbances that could be present. The final filter design resulted in a 3 dB bandwidth of 15.8908 Hz, and a null depth of 54 dB. For the baseline test case, the algorithm achieved convergence after 270 iterations. The final hardware implementation was successfully verified against the MATLAB simulation results. A speedup of 3.8 was seen between the Xilinx Virtex-5 and Spartan-II device technologies. The final design used a small fraction of the available resources for each of the two devices that were characterized. This would allow the component to be more readily available to be added to existing projects, or further optimized by utilizing additional logic