Feed-Forward Active Noise Control System Using Microphone Array

Feedforward active noise control(ANC) system are widely used to reduce the wide-band noise in different application. In feedforward ANC systems, when the noise source is unknown, the misplacement of the reference microphone may violate the causality constraint. We present a performance analysis of the feedforward ANC system under a noncausal condition. The ANC system performance degrades when the degree of noncausality increases. This research applies the microphone array technique to feedforward ANC systems to solve the unknown noise source problem. The generalized cross-correlation(GCC) and steering response power(SRP) methods based on microphone array are used to estimate the noise source location.Then, the ANC system selects the proper reference microphone for a noise control algorithm. The simulation and experiment results show that the SRP method can estimate the noise source direction with 84% accuracy. The proposed microphone array integrated ANC system can dramatically improve the system performance.

Infant Cry Language Analysis and Recognition:An Experimental Approach

Recently, lots of research has been directed towards natural language processing. However, the baby's cry, which serves as the primary means of communication for infants, has not yet been extensively explored, because it is not a language that can be easily understood. Since cry signals carry information about a babies' wellbeing and can be understood by experienced parents and experts to an extent, recognition and analysis of an infant's cry is not only possible, but also has profound medical and societal applications. In this paper, we obtain and analyze audio features of infant cry signals in time and frequency domains.Based on the related features, we can classify given cry signals to specific cry meanings for cry language recognition. Features extracted from audio feature space include linear predictive coding(LPC), linear predictive cepstral coefficients(LPCC),Bark frequency cepstral coefficients(BFCC), and Mel frequency cepstral coefficients(MFCC). Compressed sensing technique was used for classification and practical data were used to design and verify the proposed approaches. Experiments show that the proposed infant cry recognition approaches offer accurate and promising results.

Ear Field Adaptive Noise Control for Snoring:An Real-time Experimental Approach

In this paper, an active noise control(ANC) system is developed to provide an effective and non-intrusive solution for reducing loud snoring to provide a quiet environment for a snorer's bed partner. An adaptive least mean square(LMS)algorithm optimized for different kinds of snore signals is introduced and theoretically analyzed. Also, a residual noise masking approach is proposed to further reduce the effect of the snore noise without interfering with the LMS algorithm. Computer simulations followed by real-time experiments are conducted to demonstrate the feasibility of the snore ANC systems based on a pillow setup. For the optimum effect based on the characteristics of human hearing, the performance of the proposed approach is evaluated by using the multi-channel feedforward ANC systems based on the filtered-X least mean square(FXLMS) algorithm.Compared with a traditional headboard setup for snoring noise control, the proposed snore ANC systems optimized for ear field operation yield much higher noise reduction around the ears of the snorer's bed partner.

An Intelligent Optimization Approach to Non-stationary Interference Suppression for Wireless Networks

In this paper, we propose a new technique to effectively suppress non-stationary interference signal for wireless networks. This technique combines a new scheme of interference signal estimation with the intelligent optimization projection. In order to capture interference signal's subspace, a time-varying method is used to estimate the non-stationary interference.Orthogonal polynomials are used for the basis function instead of the power of the time to reduce the computational complexity.The interference is then removed from the corrupted signal by subspace projection, resulting in less distortion to the desired signal. The performance of this approach is validated by computer simulation.