Efficient adaptive algorithm for modeling a speech signal
This paper presents a time-domain prediction error method based on Newton algorithm identification for the identification of auto regressive moving average (ARMA) models of linear structural systems. The proposed structural identification method can incorporate as much as possible structural information known a priori into the structural identification process to improve the identification accuracy. This method incorporates a recursive procedure that makes successive corrections in determining, a linear mathematical model, based on the data of observation, to represent the system considered. To avoid the practical difficulty often associated with bias prediction error measurement, a stochastic Newton method is proposed. The numerical results show that the proposed method is capable to obtain the minimal standard deviation of error prediction and the estimated parameters are closer with actual values. An application of a speech signal is provided then to identify the parameters of AR model corresponding to the speech signal.
Speech recognition in noisy conditions using missing feature approach
These Ecole polytechnique federale de Lausanne EPFL, n° 2303 (2000)Faculte des sciences et techniques de l'ingenieurLaboratoire de traitement des signaux 1Jury: Phil Green, Jean-Pierre Martens, Philippe Robert, Christian Wellekens Public defense: 2000-12-8 Reference doi:10.5075/epfl-thesis-2303Print copy in library catalog Record created on 2005-03-16, modified on 2016-08-08
Novel polymeric hydrogel composites: Synthesis, physicochemical, mechanical and biocompatible properties
In this research study, novel hydrogel composite films were constructed using different ratios of poly (vinyl alcohol) (PVA)/kappa-carrageenan (KC) (PVA90/KC10%, PVA80/KC20%, PVA70/KC30%, PVA60/KC40%) crosslinked with glutaraldehyde (0.025%) and investigated their physicochemical characteristics such as mechanical, thermal, morphological, swelling behaviour, and cell viability. SEM and FTIR revealed that surface morphology changed to heterogeneous and the presence of molecular interaction among the polymers. PVA90KC10 and PVA60KC40 exhibited smaller and larger pores on surface respectively. The change in the proportion of PVA and KC also triggered the tensile strength (Ts) of the film and the highest Ts observed were 21.60 MPa for PVA60KC40. Moreover, the thermal analysis showed three-phase degradation, and an increase in KC40 concentration results inversely proportional to a decrease in the rate of thermal degradation. Further, swelling and in-vitro biodegradation study confirmed the enhanced perseverance of water uptake for PVA60KC40 (286%) due to pores structure of the hydrogel film and PVA and KC alone degraded faster as compare to other films results suggested higher concentration of PVA90KC10 showed lower degradation rate and highest for PVA60KC40 about 6% and 22% respectively. Further, the cell viability was studied with MTT assay method by using NIH3T3 and HEK-293 cells for biocompatibility study revealed NIH3T3 cells were more biocompatible than HEK-293 and cell viability percent for PVA60KC40 showed the highest cell attachment about 99%. Overall corroborating data obtained from the study attested to the average swelling, appreciable mechanical characters, good interaction between molecules, and cell viability of the constructed PVA/KC hydrogel film, these all characters pave to be used as a potential template for biomedical applications such as tissue engineering and drug delivery.