Computer-assisted detection and segmentation of blood vessels in angiography are crucial for endovascular treatments and embolization. In this article, I give an overview of the image segmentation methods using the fe...
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Computer-assisted detection and segmentation of blood vessels in angiography are crucial for endovascular treatments and embolization. In this article, I give an overview of the image segmentation methods using the features developed recently at our laboratory. Our current research directions are also highlighted
A Localized Plasma Confinement (LPC) CVD method was newly developed. The special cathode, which has periodically arranged pyramid-nozzles and pumping holes, enables stable plasma generation under very high-pressure (1...
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ISBN:
(纸本)1424400163
A Localized Plasma Confinement (LPC) CVD method was newly developed. The special cathode, which has periodically arranged pyramid-nozzles and pumping holes, enables stable plasma generation under very high-pressure (1,000-2,000Pa) conditions. We could fabricate uniform and high quality muc-Si films with very high deposition rates and very high gas utilization efficiencies by using LPC-CVD. The maximum deposition rates of 4.1 nm/s for muc-Si and 5.7 nm/s for a-Si have been also achieved. This method is expected to be effective for larger-area deposition
This paper presents a system for recognition of voiced segments in Spanish esophageal speech. It exposes different algorithms for the feature extraction of speech segment like formant analysis, linear prediction coeff...
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This paper presents a system for recognition of voiced segments in Spanish esophageal speech. It exposes different algorithms for the feature extraction of speech segment like formant analysis, linear prediction coefficients (LPC) and mel frequency cepstral coefficients (MFCC), as well as, the recognition stage through the hidden Markov models. Simulation results are presented for normal and esophageal speech. The system was implemented in a real time processing platform based on a digital signal processor TMS320C5416 of Texas Instruments
It is well known that the LPC (linear predictive coding) is a powerful tool for processing speech signals, and in this article we show that piecewise linearpredictive coefficients obtained by the competitive associat...
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It is well known that the LPC (linear predictive coding) is a powerful tool for processing speech signals, and in this article we show that piecewise linearpredictive coefficients obtained by the competitive associative nets called CAN2 can reproduce vowel signals better than the LPC. Furthermore, we present three distance measures for the CAN2 to recognize vowels, and we examine and analyze the recognition performance via the present measures and the relationship to the LPC
A hybrid neural network is proposed and implemented. The proposed network is a linear hierarchical network which consists of two subnetworks. The first subnetwork is based on Kohonen Self-Organizing Map. The second su...
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A hybrid neural network is proposed and implemented. The proposed network is a linear hierarchical network which consists of two subnetworks. The first subnetwork is based on Kohonen Self-Organizing Map. The second subnetwork is based on Learning Vector Quantization. The hybrid neural network is tested and used for Arabic phoneme recognizer.
In this paper, the signal processing technology of EM precursors for predicting earthquakes is discussed. The observed signals contain local signals related to earthquakes as well as global background noise which is s...
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In this paper, the signal processing technology of EM precursors for predicting earthquakes is discussed. The observed signals contain local signals related to earthquakes as well as global background noise which is stronger than the local signals. A method of global noise elimination by independent component analysis (ICA) is discussed. The second signal processing is to extract the sign of anomaly relevant to earthquake prediction. For the processing, the linear predicting coefficient (LPC) method is applied. The LPC error is well acknowledged as a precursor of large earthquakes exceeding magnitude seven
We present a system for text independent speaker recognition in a noise free environment, combining wavelet transforms and mel cepstral coefficients for the extraction of characteristic vectors based on modelling by G...
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We present a system for text independent speaker recognition in a noise free environment, combining wavelet transforms and mel cepstral coefficients for the extraction of characteristic vectors based on modelling by Gaussian mixture models
This paper presents speech signal modeling techniques that are well suited to robust recognition of connected digits in noisy environments. After several preprocessing steps speech is represented by a block-encoding o...
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This paper presents speech signal modeling techniques that are well suited to robust recognition of connected digits in noisy environments. After several preprocessing steps speech is represented by a block-encoding of discrete cosine transform of its spectra. In this paper we combine linear predictive coding (LPC), morphological filtering, and long block lengths to achieve robust features for improved recognition in noisy environments. The spectral envelope is first estimated by LPC. Subsequent morphological filtering enhances the peaks while smoothing the valleys, which are more affected by noise in the signal. These techniques were tested with the Aurora 2 database and the standard HMM recognizer as defined by the ETSI STQ-AURORA DSR Working group for WI007. With no major increase in computational demand a 23% word error rate (WER) reduction has been achieved as compared to the WI007 baseline MFCC front-end for multi-condition training condition. The basic conclusion is that the features resulting from the methods presented here perform better than cepstral features for ASR of noisy speech
The objective of this research and paper is an introduction to multimedia signals compressions under ISDN. Compression and following expansion, in agreement with standard, will be simulate with the help of programme M...
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The objective of this research and paper is an introduction to multimedia signals compressions under ISDN. Compression and following expansion, in agreement with standard, will be simulate with the help of programme MATLAB. Author's contribution is codec G.723.1 by MATLAB simulation. The ITU-T block structure is observed. Codec realization in MATLAB is applied on test speech signal and results were indicated in this research and paper. Graphics results are one part of research, in the paper is not enough place for this description. Presentation paper contains results of simulation in MATLAB programme for audiocodec by the recommendation G.723.1. This recommendation is used for ISDN as example and although ISDN is now replaced by xDSL, software base used for source encoding is available also for the future
Patients who have undergone a laryngectomy as a result of larynx cancer have extremely low intelligibility. This is due to the removal of their vocal fold, which forces them to use the air flowing through the esophagu...
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Patients who have undergone a laryngectomy as a result of larynx cancer have extremely low intelligibility. This is due to the removal of their vocal fold, which forces them to use the air flowing through the esophagus: this is known as esophageal speech. Measurement of formant, in vowels, in a speech signal presents significant errors when conventional techniques such as linear prediction coefficients (LPC) are used. In this paper, an accurate formant location algorithm is presented. Taking the wavelet transform as base technique, each formant subband is approximated. After locating the approximated subband, a triband analysis is applied over it. With the accurate calculation of formants, it will be possible to apply techniques which improve voice quality in correction: the position of those formants and the instabilities that present their temporal evolution in esophageal voices
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