Shock tube study of JP-10 ignition delay time

JP-10 (exo-tetrahydrodicyclopentadiene, C10H16) ignition delay times were measured in a preheated shock tube. The vapor pressures of the JP-10 were measured directly by using a high-precision vacuum gauge, to remedy the difficulty in determining the gaseous concentrations of heavy hydrocarbon fuel arising from the adsorption on the wall in shock tube experiments. The whole variation of pressure and emission of the OH or CH radicals were observed in the ignition process by a pressure transducer and a photomultiplier with a monochromator. The emission of the OH or CH radicals was used to identify the time to ignition. Experiments were performed over the pressure range of 151-556 kPa, temperature range of 1000-2100 K, fuel concentrations of 0.1%-0.55% mole fraction, and stoichiometric ratios of 0.25, 0.5, 1.0 and 2.0. The experimental results show that for the lower and higher temperature ranges, there are different dependency relationships of the ignition time on the temperature and the concentrations of JP-10 and oxygen.

A delay model for noise-induced bi-directional switching

Many biological systems can switch between two distinct states. Once switched, the system remains stable for a period of time and may switch back to its original state. A gene network with bistability is usually required for the switching and stochastic effect in the gene expression may induce such switching. A typical bistable system allows one-directional switching, in which the switch from the low state to the high state or from the high state to the low state occurs under different conditions. It is usually difficult to enable bi-directional switching such that the two switches can occur under the same condition. Here, we present a model consisting of standard positive feedback loops and an extra negative feedback loop with a time delay to study its capability to produce bi-directional switching induced by noise. We find that the time delay in the negative feedback is critical for robust bi-directional switching and the length of delay affects its switching frequency.

The effect of the group delay ripple of chirped fiber grating on composite second-order in optical fiber CATV system

The effect of group delay ripple of chirped fiber gratings on composite second-order (CSO) performance in optical fiber CATV system is investigated. We analyze the system CSO performances for different ripple amplitudes, periods and residual dispersion amounts in detail. It is found that the large ripple amplitude and small ripple period will deteriorate the system CSO performance seriously. Additionally, the residual dispersion amount has considerable effect on CSO performance in the case of small ripple amplitude and large ripple period. (c) 2004 Elsevier B.V. All rights reserved.

Group delay dispersion measurement of Yb : Gd2SiO5, Yb : GdYSiO5 and Yb : LuYSiO5 crystal with white-light interferometry

We report the measured group delay dispersion (GDD) of new crystals Yb:Gd2SiO5 (Yb:GSO), Yb:GdYSiO5 (Yb:GYSO) and Yb:LuYSiO5 (Yb:LYSO) over wavelengths from 1000nm to 1200nm, with a white-light interferometer. Those GDD data should be useful for the dispersion compensation for femtosecond pulse generation in the lasers with these new crystals as the gain media. (C) 2007 Optical Society of America

Characteristic analysis of the optical delay in frequency response of resonant cavity enhanced (RCE) photodetectors

With consideration of the modulation frequency of the input lightwave itself, we present a new model to calculate the quantum efficiency of RCE p-i-n photodetectors (PD) by superimposition of multiple reflected lightwaves. For the first time, the optical delay, another important factor limiting the electrical bandwidth of RCE p-i-n PD excluding the transit time of the carriers and RCd response of the photodetector, is analyzed and discussed in detail. The optical delay dominates the bandwidth of RCE p-i-n PD when its active layer is thinner than several 10 nm. These three limiting factors must be considered exactly for design of ultra-high-speed RCE p-i-n PD.

Calculation of light delay for coupled microrings by FDTD technique and Pade approximation

The Pade approximation with Baker's algorithm is compared with the least-squares Prony method and the generalized pencil-of-functions (GPOF) method for calculating mode frequencies and mode Q factors for coupled optical microdisks by FDTD technique. Comparisons of intensity spectra and the corresponding mode frequencies and Q factors show that the Pade approximation can yield more stable results than the Prony and the GPOF methods, especially the intensity spectrum. The results of the Prony method and the GPOF method are greatly influenced by the selected number of resonant modes, which need to be optimized during the data processing, in addition to the length of the time response signal. Furthermore, the Pade approximation is applied to calculate light delay for embedded microring resonators from complex transmission spectra obtained by the Pade approximation from a FDTD output. The Prony and the GPOF methods cannot be applied to calculate the transmission spectra, because the transmission signal obtained by the FDTD simulation cannot be expressed as a sum of damped complex exponentials. (C) 2009 Optical Society of America

All-optical continuously tunable delay with a high linear-chirp-rate fiber Bragg grating based on four-wave mixing in a highly-nonlinear photonic crystal fiber

A scheme for hi-fi all-optical continuously tunable delay is proposed. The signal wavelength is converted to a desired idler wavelength and converted back after being delayed by a high linear-chirp-rate (HLCR) fiber Bragg grating (FBG) based on four-wave mixing (FWM) in a highly-nonlinear photonic crystal fiber (HN-PCF). In our experiment, 400 ps (more than 8 full width of half maximum, FWHM) tunable delay is achieved for a 10 GHz clock pulse with relative pulse width broaden ratio (RPWBR) of 2.08%. The power penalty is only 0.3 dB at 10(-9) BER for a 10 Gb/s 2(31)-1 pseudo random bit sequence (PRBS) data. (c) 2009 Elsevier B.V. All rights reserved.

Determining of the delay time for a heating ventilating and air-conditioning plant using two weighted neural network approach

This paper presents an two weighted neural network approach to determine the delay time for a heating, ventilating and air-conditioning (HVAC) plan to respond to control actions. The two weighted neural network is a fully connected four-layer network. An acceleration technique was used to improve the General Delta Rule for the learning process. Experimental data for heating and cooling modes were used with both the two weighted neural network and a traditional mathematical method to determine the delay time. The results show that two weighted neural networks can be used effectively determining the delay time for AVAC systems.

Digits speech recognition based on geometrical learning

We investigate the use of independent component analysis (ICA) for speech feature extraction in digits speech recognition systems.We observe that this may be true for a recognition tasks based on geometrical learning with little training data. In contrast to image processing, phase information is not essential for digits speech recognition. We therefore propose a new scheme that shows how the phase sensitivity can be removed by using an analytical description of the ICA-adapted basis functions via the Hilbert transform. Furthermore, since the basis functions are not shift invariant, we extend the method to include a frequency-based ICA stage that removes redundant time shift information. The digits speech recognition results show promising accuracy, Experiments show method based on ICA and geometrical learning outperforms HMM in different number of train samples.

Information geometry theory of high-dimension space and application for speaker independent continuous digit speech recognition

In the light of descriptive geometry and notions in set theory, this paper re-defines the basic elements in space such as curve and surface and so on, presents some fundamental notions with respect to the point cover based on the High-dimension space (HDS) point covering theory, finally takes points from mapping part of speech signals to HDS, so as to analyze distribution information of these speech points in HDS, and various geometric covering objects for speech points and their relationship. Besides, this paper also proposes a new algorithm for speaker independent continuous digit speech recognition based on the HDS point dynamic searching theory without end-points detection and segmentation. First from the different digit syllables in real continuous digit speech, we establish the covering area in feature space for continuous speech. During recognition, we make use of the point covering dynamic searching theory in HDS to do recognition, and then get the satisfying recognized results. At last, compared to HMM (Hidden Markov models)-based method, from the development trend of the comparing results, as sample amount increasing, the difference of recognition rate between two methods will decrease slowly, while sample amount approaching to be very large, two recognition rates all close to 100% little by little. As seen from the results, the recognition rate of HDS point covering method is higher than that of in HMM (Hidden Markov models) based method, because, the point covering describes the morphological distribution for speech in HDS, whereas HMM-based method is only a probability distribution, whose accuracy is certainly inferior to point covering.

Mandarin speech emotion recognition based on high dimensional geometry theory

In this paper, a novel approach for mandarin speech emotion recognition, that is mandarin speech emotion recognition based on high dimensional geometry theory, is proposed. The human emotions are classified into 6 archetypal classes: fear, anger, happiness, sadness, surprise and disgust. According to the characteristics of these emotional speech signals, the amplitude, pitch frequency and formant are used as the feature parameters for speech emotion recognition. The new method called high dimensional geometry theory is applied for recognition. Compared with traditional GSVM model, the new method has some advantages. It is noted that this method has significant values for researches and applications henceforth.

Research on continuous speech recognition with small vocabulary based on biomimetic pattern recognition

Based on biomimetic pattern recognition theory, we proposed a novel speaker-independent continuous speech keyword-spotting algorithm. Without endpoint detection and division, we can get the minimum distance curve between continuous speech samples and every keyword-training net through the dynamic searching to the feature-extracted continuous speech. Then we can count the number of the keywords by investigating the vale-value and the numbers of the vales in the curve. Experiments of small vocabulary continuous speech with various speaking rate have got good recognition results and proved the validity of the algorithm.

Determining of the delay time for a heating ventilating and air-conditioning plant using multi-weights neurons approach

This paper presents an multi weights neurons approach to determine the delay time for a Heating ventilating and air-conditioning (HVAC) plan to respond to control actions. The multi weights neurons is a fully connected four-layer network. An acceleration technique was used to improve the general delta rule for the learning process. Experimental data for heating and cooling modes were used with both the multi weights neurons and a traditional mathematical method to determine the delay time. The results show that multi weights neurons can be used effectively determining the delay time for HVAC systems.

A speaker-independent continuous speech recognition system using biomimetic pattern recognition

In speaker-independent speech recognition, the disadvantage of the most diffused technology (HMMs, or Hidden Markov models) is not only the need of many more training samples, but also long train time requirement. This paper describes the use of Biomimetic pattern recognition (BPR) in recognizing some mandarin continuous speech in a speaker-independent manner. A speech database was developed for the course of study. The vocabulary of the database consists of 15 Chinese dish's names, the length of each name is 4 Chinese words. Neural networks (NNs) based on Multi-weight neuron (MWN) model are used to train and recognize the speech sounds. The number of MWN was investigated to achieve the optimal performance of the NNs-based BPR. This system, which is based on BPR and can carry out real time recognition reaches a recognition rate of 98.14% for the first option and 99.81% for the first two options to the persons from different provinces of China speaking common Chinese speech. Experiments were also carried on to evaluate Continuous density hidden Markov models (CDHMM), Dynamic time warping (DTW) and BPR for speech recognition. The Experiment results show that BPR outperforms CDHMM and DTW especially in the cases of samples of a finite size.