Fa-Long Luo

Adaptive null-forming scheme in digital hearing aids

We propose an effective adaptive null-forming scheme for two nearby microphones in endfire orientation that are used in digital hearing aids and in many other hearing devices. This adaptive null-forming scheme is mainly based on an adaptive combination of two fixed polar patterns that act to make the null of the combined polar pattern of the system output always be toward the direction of the noise. The adaptive combination of these two fixed polar patterns is accomplished by simply updating an adaptive gain following the output of the first polar pattern unit. The value of this gain is updated by minimizing the power of the system output, and related adaptive algorithms to update this gain are also given. We have implemented this proposed system on the basis of a programmable DSP chip and performed various tests. Theoretical analyses and testing results demonstrated the effectiveness of the proposed system and the accuracy of its implementation.

A minor subspace analysis algorithm

This paper proposes a learning algorithm which extracts adaptively the minor subspace spanned by the eigenvectors corresponding to the smallest eigenvalues of the autocorrelation matrix of an input signal. We show both analytically and by simulation results that the weight vectors provided by the proposed algorithm are guaranteed to converge to the minor subspace of the input signal. For wider applications, we also present the complex valued version of the proposed minor subspace analysis algorithm.

Spectral contrast enhancement: algorithms and comparisons

This paper investigates spectral contrast enhancement techniques and their implementation complexity. Three algorithms are dealt with in this paper. The first is the method described by Baer, Moore and Gatehouse. Two alternative methods are also proposed and investigated in this paper from a practical application and implementation point of view. Theoretical analyses and results from laboratory, simulation and subject listening show that spectral contrast enhancement and performance improvement can be achieved by use of these three methods with the appropriate selection of their relevant parameters.

Signal processing for 5G : algorithms and implementations

Signal processing techniques have played the most important role in wireless communications since the second generation of cellular systems. It is anticipated that new techniques employed in 5G wireless networks will not only improve peak service rates significantly, but also enhance capacity, coverage, reliability , low-latency, efficiency, flexibility, compatibility and convergence to meet the increasing demands imposed by applications such as big data, cloud service, machine-to-machine (M2M) and mission-critical communications.

A generalized learning algorithm of minor component

This paper proposes a generalized nonlinear minor component analysis algorithm. First, we will prove that with appropriate nonlinear functions the proposed algorithm can extract adaptively the minor component. Then we will discuss how to choose the related nonlinear functions so as to guarantee the desired convergence. Furthermore, we will show that all the other available minor component analysis algorithms are special cases of this proposed generalized algorithm. Finally, the complex-valued version of the proposed algorithm will be given in this paper for wider applications. In addition, this proposed minor component analysis algorithm can also be used to extract the principal component by simply reversing the sign of the corresponding terms.

Dynamic analog resonator-based adaptive filters

Dynamic analog building blocks (integrator, tunable gain stage) with high performance are proposed and analyzed. They exhibit low sensitivities to the component non-idealities (amplifier DC gain, amplifier and multiplier offset voltage, ...) and operate in double-sampled mode. Issues concerning the design of resonator based adaptive filters using the proposed structures are discussed. Numerical results obtained from a proof-of-concept prototype validate the proposed design method.

A CMOS front-end architecture for hard-disk drive read-channel equalizer

The functional characteristics and design challenges associated with the different building blocks of a CMOS front-end architecture for hard disk drive read-channel equalizer are presented. These include the mixed-signal design of a variable gain amplifier, a continuous-time low-pass filter, data converters and clock generation and recovery circuits. With a realistic computer model of the system, the analysis of structural variations and effects of component nonidealities becomes feasible. Numerical results show that circuit techniques that minimize sensitivity to power-supply and substrate noise, while maintaining the power dissipation and parameter tuning range are critical.

Editorial: special issue on speech processing for hearing aids

With the widespread usage of digital hearing aids and increased demands placed on their performance, advanced speech processing techniques are playing a more important role in modern hearing aid systems. Speech processing for hearing aids encompasses a range of topics including signal acquisition, transfer, amplification, transmission, measurement, filtering, parameter estimation, separation, detection, enhancement and classification. Speech processing techniques for hearing aids are also highly applicable to and benefited by the characterization and modeling of hearingimpaired auditory systems. We believe that speech processing in hearing aids can be primarily divided into three application areas. The first area is devoted to using advanced speech signal processing techniques to characterize and compensate for various hearing impairments. An example of such a technique is the use of perceptual-modelbased multi-band compression and amplification to compensate for the loss in loudness, and the use of spectral contrast enhancement to compensate for the loss of frequency selectivity. Because hearing-impaired individuals experience more difficulty understanding speech in noise than normal-hearing people, the second area of speech processing research in hearing aids is effective target signal enhancement and noise reduction. The third area focuses on the real-world use of hearing aids; addressing issues such as flexibility, convenience, feedback cancellation, and artifact reduction. Because of the limitations imposed by the hardware requirements, computational speed, power supply and other practical factors, the development and implementation of speech processing techniques for hearing aids has been a challenging and active area of research over the past decade. The intention of this special issue is to stimulate and guide the development of new and improved hearing aids by providing a high quality forum for scientists and engineers interested in hearing-aid design to learn about recent developments. In addition, it is hoped that the issue will attract a broad audience in the speech processing community. The call for papers for this issue resulted in a large quantity of excellent submissions from around the world. After two rounds of careful reviews from approximately forty experts in related fields, eleven papers, organized into four groups, were selected to be included in this special issue. Three papers in the first group focus on speech processing algorithms based on characterizations of auditory systems and comparisons between hearing-impaired people and normal-hearing people. The paper by Lisa G. Huettel and Leslie M. Collins investigates the differences between normal and impaired auditory processing on a frequency discrimination task by analyzing the responses of a computational auditory model using signal detection theory. Hearing impairments that were simulated can be characterized by a threshold shift, damage to the outer hair cells, and impaired neural synchrony. Two kinds of detectors are designed and implemented in the paper. Although a simple hearing aid is simulated in this paper for further analysis and evaluation, the proposed approach could be used to evaluate the design of more complex hearing aids. The second paper in this group is by Thomas Fillon and Jacques Prado. In this paper, the authors present an implementation of the EMSR (Ephraim and Malah Suppression Rule) on Speech Communication 39 (2003) 1–3 www.elsevier.com/locate/specom

The exponential stability of the invariant-norm PCA algorithm

This brief investigates a recently proposed principal component analysis (PCA) algorithm. We prove that that the solutions of the corresponding differential equations converge to the principal eigenvectors of the autocorrelation matrix and calculate an exponential decaying bound for the error.

Design of a high-frequency second-order /spl Delta//spl Sigma/ modulator

As the minimum feature size of VLSI technologies scales down, more of the signal processing tasks are performed in the digital domain, making the analog-to-digital converter (ADC) design critical. High speed designs can be achieved by using oversampling ADC structures. At high sampling rates, the resolution appears to be limited by amplifier settling requirements. Design techniques to improve the ADC performance are presented. The proposed modulator structure uses the double-sampled technique, which increases by a factor of two the maximum speed of operation and correctly operates even with low DC gain amplifiers.