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Matrix Consisting (matrix + consisting)
Selected AbstractsA multi-user CDMA receiver utilizing decorrelating detector with additional dummy pilot responseINTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, Issue 3 2003Mitsuhiro Tomita Abstract A pilot assisted CDMA system which uses extended spreading sequences with guard sequences under a quasi-synchronous condition is capable of separating the interference components included in the input of a de-correlating receiver by solving a system of linear equations. The performance of such a system, however, depends on the property of the de-correlating matrix consisting of the received pilots, which correspond to the respective user spreading sequences and the multi-path channel conditions. That is, the regularity of the matrix often tends to degrade, and the rank reduces occasionally primarily due to the multi-paths, resulting in solutions that are vulnerable to AWGN. The present paper proposes an effective technique to solve this problem by introducing a virtual user into a group of real users that are to be served. The simulation results indicate a remarkable improvement in the bit-error-rate (BER) performance. In addition, based on the BER performance, the system has a RAKE-like function that has power-sum characteristics. Copyright © 2003 John Wiley & Sons, Ltd. [source] ,-Carotene-Loaded Nanostructured Lipid CarriersJOURNAL OF FOOD SCIENCE, Issue 2 2008A. Hentschel ABSTRACT:, Nanostructured lipid carriers (NLC) technology was used to disperse hydrophobic ,-carotene in an aqueous phase. NLC are lipid nanoparticles with a particle matrix consisting of a blend of a liquid and solid lipid. They were produced by melting the lipid blend at 80 °C and dispersing it into a hot emulsifier solution. The aim of this study was to extend the limited knowledge of melt-emulsified lipidic colloids in food systems and to evaluate the feasibility for further applications as functional ingredient in beverages. Physical stability of the NLC suspension was examined at 2 different storage temperatures by measuring the particle size with photon correlation spectroscopy (PCS) and laser diffractometry (LD). All particles containing sufficient amounts of emulsifier were smaller than 1 ,m (LD diameter 100%) at a mean particle size of around 0.3 ,m (LD) for 9 wk at 20 °C and at least 30 wk at 4 to 8 ° C. Differential scanning calorimetry (DSC) was used to study the solid state of the lipids both in the ,-carotene loaded PGMS and in the NLC particles. Propylene glycol monostearate (PGMS) when dispersed as NLC recrystallized up to 98% during storage time. Within the regarded period of 7 mo no polymorph transitions were observed. Furthermore, stability of the ,-carotene in water dependent on NLC concentration and tocopherol content was measured photospectrometrically to get an estimation of the behavior of NLC in beverages. [source] Comparison of Principal Analysis and the Tucker3 ModelMOLECULAR INFORMATICS, Issue 4 2003A Case Study Abstract A three-ways array data matrix consisting of the activity data of laccase enzyme has been evaluated by both principal component analyses (PCA) and Tucker3 model. Activity data have been determined in 28 culture media, at 6 sampling times and by four strains of Lentinus edodes. PCA has been carried out three times one of the factors being always the variables and the other two factors being the observations. The dimensionality of the matrices of loadings calculated by PCAs and those of component matrices of Tucker3 model has been reduced to two by the nonlinear mapping technique. It has been found that the dimensionality of component matrices for Tucker3 model can be predicted from the results of PCAs. Linear regression analyses indicated that the distribution of the original data points on the two-dimensional nonlinear maps considerably depends on the fact that the data have been calculated by PCA or by Tucker3 model. [source] Fault detection and isolation for dynamic processes using recursive principal component analysis (PCA) based on filtering of signalsASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING, Issue 6 2007Jyh-Cheng Jeng Abstract A systematic procedure for the fault detection and isolation of dynamic systems is presented. The inputs of the process first pass through the dynamic filters which represent the process dynamics. Then, principal component analysis (PCA) is applied to the data matrix consisting of these filtered signals and the process outputs for fault detection. In case of a fault being detected, owing to an artificial linear relationship existing in the data matrix, the last principal component (LPC) is adopted for fault isolation. A recursive algorithm for PCA based on rank-one matrix update of the covariance is derived to compute the LPC on line. Patterns of the LPC are devised to isolate these faults, which include constant-bias and high-frequency noises originating from sensor measurement, errors resulting from input disturbance and change in the process gain. Furthermore, the magnitude of the fault can also be identified from the computed LPC. An illustrative example is used to verify the effectiveness of the proposed method. Copyright © 2007 Curtin University of Technology and John Wiley & Sons, Ltd. [source] | ||||||||||