The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Fan Gang Zeng - One of the best experts on this subject based on the ideXlab platform.

  • encoding frequency modulation to improve cochlear implant performance in noise
    IEEE Transactions on Biomedical Engineering, 2005
    Co-Authors: Ginger S. Stickney, Fan Gang Zeng
    Abstract:

    Different from traditional Fourier analysis, a signal can be decomposed into amplitude and frequency modulation components. The speech Processing Strategy in most modern cochlear implants only extracts and encodes amplitude modulation in a limited number of frequency bands. While amplitude modulation encoding has allowed cochlear implant users to achieve good speech recognition in quiet, their performance in noise is severely compromised. Here, we propose a novel speech Processing Strategy that encodes both amplitude and frequency modulations in order to improve cochlear implant performance in noise. By removing the center frequency from the subband signals and additionally limiting the frequency modulation's range and rate, the present Strategy transforms the fast-varying temporal fine structure into a slowly varying frequency modulation signal. As a first step, we evaluated the potential contribution of additional frequency modulation to speech recognition in noise via acoustic simulations of the cochlear implant. We found that while amplitude modulation from a limited number of spectral bands is sufficient to support speech recognition in quiet, frequency modulation is needed to support speech recognition in noise. In particular, improvement by as much as 71 percentage points was observed for sentence recognition in the presence of a competing voice. The present result strongly suggests that frequency modulation be extracted and encoded to improve cochlear implant performance in realistic listening situations. We have proposed several implementation methods to stimulate further investigation.

  • a novel speech Processing Strategy incorporating tonal information for cochlear implants
    IEEE Transactions on Biomedical Engineering, 2004
    Co-Authors: Ning Lan, Kaibao Nie, S K Gao, Fan Gang Zeng
    Abstract:

    Good performance in cochlear implant users depends in large part on the ability of a speech processor to effectively decompose speech signals into multiple channels of narrow-band electrical pulses for stimulation of the auditory nerve. Speech processors that extract only envelopes of the narrow-band signals (e.g., the continuous interleaved sampling (CIS) processor) may not provide sufficient information to encode the tonal cues in languages such as Chinese. To improve the performance in cochlear implant users who speak tonal language, we proposed and developed a novel speech-Processing Strategy, which extracted both the envelopes of the narrow-band signals and the fundamental frequency (F/sub 0/) of the speech signal, and used them to modulate both the amplitude and the frequency of the electrical pulses delivered to stimulation electrodes. We developed an algorithm to extract the fundamental frequency and identified the general patterns of pitch variations of four typical tones in Chinese speech. The effectiveness of the extraction algorithm was verified with an artificial neural network that recognized the tonal patterns from the extracted F/sub 0/ information. We then compared the novel Strategy with the envelope-extraction CIS Strategy in human subjects with normal hearing. The novel Strategy produced significant improvement in perception of Chinese tones, phrases, and sentences. This novel processor with dynamic modulation of both frequency and amplitude is encouraging for the design of a cochlear implant device for sensorineurally deaf patients who speak tonal languages.

Fritz Aldinger - One of the best experts on this subject based on the ideXlab platform.

  • preparation of si3n4 ceramics with high strength and high reliability via a Processing Strategy
    Journal of The European Ceramic Society, 2002
    Co-Authors: Longjie Zhou, Yong Huang, Zhipeng Xie, Andre Zimmermann, Fritz Aldinger
    Abstract:

    Abstract In this study, the preparation of Si 3 N 4 ceramics with high mechanical reliability is investigated. The influences of several Processing steps on the bending strength and the Weibull modulus are reported including: (i) coating of the Si 3 N 4 powder with its sintering aids, (ii) oxidation of the coated powder, (iii) cold isostatic pressing, (iv) gelcasting of the green bodies and (v) gas pressure sintering. It was found that all the aforementioned steps contribute to improvements of strength and reliability of Si 3 N 4 ceramics. Via an optimised Processing Strategy, Si 3 N 4 ceramics with a bending strength and a Weibull modulus as high as 944.7±29.5 MPa and 33.9, respectively, could be prepared. Additionally, it was also found that surface modifications, i.e. coating and oxidation of Si 3 N 4 powder, increased the rheological properties of the powder suspension in aqueous media, which is favourable for in situ colloidal forming such as gelcasting.

Jian Wang - One of the best experts on this subject based on the ideXlab platform.

  • a combination forecasting approach applied in multistep wind speed forecasting based on a data Processing Strategy and an optimized artificial intelligence algorithm
    Applied Energy, 2018
    Co-Authors: Zhongshan Yang, Jian Wang
    Abstract:

    Abstract Owing to the complexity and uncertainty of wind speed, accurate wind speed prediction has become a highly anticipated and challenging problem in recent years. Researchers have conducted numerous studies on wind speed prediction theory and practice; however, research on multi-step wind speed prediction remains scarce, which hinders further development in this area. To improve upon the accuracy and stability of multi-step wind speed prediction, this paper proposes a combination model based on a data preProcessing Strategy, an improved optimization model, a no negative constraint theory, and several single prediction models. To improve upon forecasting performance, an improved water cycle algorithm based on a quasi-Newton algorithm is proposed to optimize the weight coefficients of the single models. In the empirical research, 10-min and 30-min wind speed data from Shandong Province in China, collected for case studies, were used to assess the comprehensive performance of the proposed combination model. Finally, we used 10-fold cross-validation and multiple error criteria to evaluate the comprehensive performance of the proposed combination model. The simulation results indicate that (a) the quasi-Newton algorithm can effectively increase the diversity of the water cycle algorithm particles, resulting in improved water cycle algorithm optimization performance; (b) the combination model exhibits superior predictive performance to a single model by taking advantage of each single model; and (c) the proposed combination model can effectively improve multi-step wind speed prediction results.

  • a hybrid forecasting approach applied in wind speed forecasting based on a data Processing Strategy and an optimized artificial intelligence algorithm
    Energy, 2018
    Co-Authors: Zhongshan Yang, Jian Wang
    Abstract:

    Abstract Conducting the accurate forecasting of wind speed is a both challenging and difficult task. However, this task is of great significance for wind farm scheduling and safe integration into the grid. In this paper, the wind speed at 10 or 30 min is predicted using only historical wind speed data. The existing single models are not enough to overcome the instability and inherent complexity of wind speed. To enhance forecasting ability, a novel hybrid model based on complementary ensemble empirical mode decomposition (CEEMD) and modified wind driven optimization is introduced for wind speed forecasting in this paper. CEEMD is utilized to decompose the original wind speed series into several intrinsic mode functions (IMFs), and each IMF is forecasted by back propagation neural network (BP). A new optimization algorithm combined Broyden family and wind driven optimization is presented and applied to optimize the initial weights and thresholds of BP. Finally, all forecasted IMFs are integrated as final forecasts. The 10min and 30min wind speed from the province of Shandong, China, were used in this paper as the case study, and the results confirm that the proposed hybrid model can improve the forecasting accuracy and stability.

Robert Cowan - One of the best experts on this subject based on the ideXlab platform.

Simon Haykin - One of the best experts on this subject based on the ideXlab platform.

  • a novel signal Processing Strategy for hearing aid design neurocompensation
    Signal Processing, 2004
    Co-Authors: Jeff Bondy, Sue Becker, Ian C Bruce, Laurel J Trainor, Simon Haykin
    Abstract:

    A novel approach to hearing-aid signal Processing is described, which attempts to re-establish a normal neural representation in the sensorineural impaired auditory system. Most hearing-aid fitting procedures are based on heuristics or some initial qualitative theory. These theories, such as loudness normalization, loudness equalization or maximal intelligibility can give vastly different results for a given individual, and each may provide variable results for different hearing impaired individuals with the same audiogram. Recent research in characterizing sensorineural hearing loss has delineated the importance of hair cell damage in understanding the bulk of sensorineural hearing impairments. A novel methodology based on restoring normal neural representation after the sensorineural impairment is presented here. This approach can be used for designing hearing-aid signal Processing algorithms, as well as providing a general, automated means of predicting the relative intelligibility of a given speech sample in normal hearing and hearing impaired subjects.