Modified Block Adaptive Predictive Coder For Speech Processing

This thesis investigated the potential use of Linear Predictive Coding in speech communication applications. A Modified Block Adaptive Predictive Coder is developed, which reduces the computational burden and complexity without sacrificing the speech quality, as compared to the conventional adaptive predictive coding (APC) system. For this, changes in the evaluation methods have been evolved. This method is as different from the usual APC system in that the difference between the true and the predicted value is not transmitted. This allows the replacement of the high order predictor in the transmitter section of a predictive coding system, by a simple delay unit, which makes the transmitter quite simple. Also, the block length used in the processing of the speech signal is adjusted relative to the pitch period of the signal being processed rather than choosing a constant length as hitherto done by other researchers. The efficiency of the newly proposed coder has been supported with results of computer simulation using real speech data. Three methods for voiced/unvoiced/silent/transition classification have been presented. The first one is based on energy, zerocrossing rate and the periodicity of the waveform. The second method uses normalised correlation coefficient as the main parameter, while the third method utilizes a pitch-dependent correlation factor. The third algorithm which gives the minimum error probability has been chosen in a later chapter to design the modified coder The thesis also presents a comparazive study beh-cm the autocorrelation and the covariance methods used in the evaluaiicn of the predictor parameters. It has been proved that the azztocorrelation method is superior to the covariance method with respect to the filter stabf-it)‘ and also in an SNR sense, though the increase in gain is only small. The Modified Block Adaptive Coder applies a switching from pitch precitzion to spectrum prediction when the speech segment changes from a voiced or transition region to an unvoiced region. The experiments cont;-:ted in coding, transmission and simulation, used speech samples from .\£=_‘ajr2_1a:r1 and English phrases. Proposal for a speaker reecgnifion syste: and a phoneme identification system has also been outlized towards the end of the thesis.

Development and Evaluation of Blind Identification Techniques for Nonlinear Systems

Identification and Control of Non‐linear dynamical systems are challenging problems to the control engineers.The topic is equally relevant in communication,weather prediction ,bio medical systems and even in social systems,where nonlinearity is an integral part of the system behavior.Most of the real world systems are nonlinear in nature and wide applications are there for nonlinear system identification/modeling.The basic approach in analyzing the nonlinear systems is to build a model from known behavior manifest in the form of system output.The problem of modeling boils down to computing a suitably parameterized model,representing the process.The parameters of the model are adjusted to optimize a performanace function,based on error between the given process output and identified process/model output.While the linear system identification is well established with many classical approaches,most of those methods cannot be directly applied for nonlinear system identification.The problem becomes more complex if the system is completely unknown but only the output time series is available.Blind recognition problem is the direct consequence of such a situation.The thesis concentrates on such problems.Capability of Artificial Neural Networks to approximate many nonlinear input-output maps makes it predominantly suitable for building a function for the identification of nonlinear systems,where only the time series is available.The literature is rich with a variety of algorithms to train the Neural Network model.A comprehensive study of the computation of the model parameters,using the different algorithms and the comparison among them to choose the best technique is still a demanding requirement from practical system designers,which is not available in a concise form in the literature.The thesis is thus an attempt to develop and evaluate some of the well known algorithms and propose some new techniques,in the context of Blind recognition of nonlinear systems.It also attempts to establish the relative merits and demerits of the different approaches.comprehensiveness is achieved in utilizing the benefits of well known evaluation techniques from statistics. The study concludes by providing the results of implementation of the currently available and modified versions and newly introduced techniques for nonlinear blind system modeling followed by a comparison of their performance.It is expected that,such comprehensive study and the comparison process can be of great relevance in many fields including chemical,electrical,biological,financial and weather data analysis.Further the results reported would be of immense help for practical system designers and analysts in selecting the most appropriate method based on the goodness of the model for the particular context.

Polypropylene/metal oxide nanocomposites: fiber spinning and evaluation”

PP has been getting much attention over the years because it is a very durable polymer commonly used in aggressive environments including automotive battery casings, fuel containers etc. They are used to make bottles, fibers for clothing, components in cars etc. However, it has some shortcomings such as low dimensional and thermal stability. Materials such as metal oxides with sizes of the order 1–50 nm have received a great deal of attention because of their versatile applications in polymer/ inorganic nanocomposites, optoelectronic devices, biomedical materials, and other areas. They are stable under harsh process conditions and also regarded as safe materials to human beings and animals. In the present investigation, PP is modified by incorporating metal oxide nanoparticles such as ZnO and TiO2 by simple melt mixing method. Melt spinning method was used to prepare PP/metal oxide nanocomposite fibers. Various studies have been carried out on these composites and fibers. In the first part of the study, ZnO nanoparticles were prepared from ZnCl2 and NaOH in presence of chitosan, PVA, ethanol and starch. This is a simple and inexpensive method compared to other methods. Change in morphology and particle size of ZnO were studied. Least particle size was obtained in chitosan medium. The particles were characterized by using XRD, SEM, TEM, TGA and EDAX. Antibacterial properties of ZnO prepared in chitosan medium (NZO) and commercial zinc oxide (CZO) were evaluated using a gram positive and a gram negative bacteria

Chemical Evaluation of Selected Organics and Trace Metals in the Mangrove Macroflora Of Cochin

Mangroves are considered to play a significant role in global carbon cycling. Themangrove forests would fix CO2 by photosynthesis into mangrove lumber and thus decrease the possibility of a catastrophic series of events - global warming by atmospheric CO2, melting of the polar ice caps, and inundation of the great coastal cities of the world. The leaf litter and roots are the main contributors to mangrove sediments, though algal production and allochthonous detritus can also be trapped (Kristensen et al, 2008) by mangroves due to their high organic matter content and reducing nature are excellent metal retainers. Environmental pollution due to metals is of major concern. This is due to the basic fact that metals are not biodegradable or perishable the way most organic pollutants are. While most organic toxicants can be destroyed by combustion and converted into compounds such as C0, C02, SOX, NOX, metals can't be destroyed. At the most the valance and physical form of metals may change. Concentration of metals present naturally in air, water and soil is very low. Metals released into the environment through anthropogenic activities such as burning of fossils fuels, discharge of industrial effluents, mining, dumping of sewage etc leads to the development of higher than tolerable or toxic levels of metals in the environment leading to metal pollution. Of course, a large number of heavy metals such as Fe, Mn, Cu, Ni, Zn, Co, Cr, Mo, and V are essential to plants and animals and deficiency of these metals may lead to diseases, but at higher levels, it would lead to metal toxicity. Almost all industrial processes and urban activities involve release of at least trace quantities of half a dozen metals in different forms. Heavy metal pollution in the environment can remain dormant for a long time and surface with a vengeance. Once an area gets toxified with metals, it is almost impossible to detoxify it. The symptoms of metal toxicity are often quite similar to the symptoms of other common diseases such as respiratory problems, digestive disorders, skin diseases, hypertension, diabetes, jaundice etc making it all the more difficult to diagnose metal poisoning. For example the Minamata disease caused by mercury pollution in addition to affecting the nervous system can disturb liver function and cause diabetes and hypertension. The damage caused by heavy metals does not end up with the affected person. The harmful effects can be transferred to the person's progenies. Ironically heavy metal pollution is a direct offshoot of our increasing ability to mass produce metals and use them in all spheres of existence. Along with conventional physico- chemical methods, biosystem approachment is also being constantly used for combating metal pollution

In vivo screening of mangrove plants for anti WSSV activity in Penaeus monodon, and evaluation of Ceriops tagal as a potential source of antiviral molecules

The objective of the study was to find out a natural way to fight white spot syndrome virus (WSSV) in cultured shrimps, as the present scenario necessitated an organic remedy for the devastating pathogen in crustaceans. Under this research programme seven mangrove plants were collected, identified and aqueous extracts screened for their protective effect on the giant tiger shrimp Penaeus monodon against WSSV. The experimental design consisted two modes of application, such as exposure of the virus to the extract and injection challenge, and oral administration of the extract coated feed followed by oral challenge. All experimental animals were monitored through a nested diagnostic PCR analysis. Of the seven mangrove extracts screened aqueous extract from Ceriops tagal imparted total protection to shrimp from WSSV when challenged by both methods. Shrimps administered with the aqueous extract from C. tagal were devoid of virions. The HPLC fingerprint of the aqueous extracts from C. tagal showed more than 25 peaks and 7 of them were larger and well separated. Preliminary phytochemical analysis revealed the presence of alkaloids, flavonoids, polyphenolics, cardiac glycosides, saponins and sterols. The study indicated suitability of the aqueous extract of C. tagal as a possible prophylaxis for WSSV infection in shrimp. This is the first report on the anti WSSV property of the mangrove plant C. tagal

An efficient scheme for the evaluation of coding performance of high speed links incorporating joint error behaviour based on Monte Carlo Method

While channel coding is a standard method of improving a system’s energy efficiency in digital communications, its practice does not extend to high-speed links. Increasing demands in network speeds are placing a large burden on the energy efficiency of high-speed links and render the benefit of channel coding for these systems a timely subject. The low error rates of interest and the presence of residual intersymbol interference (ISI) caused by hardware constraints impede the analysis and simulation of coded high-speed links. Focusing on the residual ISI and combined noise as the dominant error mechanisms, this paper analyses error correlation through concepts of error region, channel signature, and correlation distance. This framework provides a deeper insight into joint error behaviours in high-speed links, extends the range of statistical simulation for coded high-speed links, and provides a case against the use of biased Monte Carlo methods in this setting

In vivo screening of mangrove plants for anti WSSV activity in Penaeus monodon, and evaluation of Ceriops tagal as a potential source of antiviral molecules

The objective of the study was to find out a natural way to fight white spot syndrome virus (WSSV) in cultured shrimps, as the present scenario necessitated an organic remedy for the devastating pathogen in crustaceans. Under this research programme seven mangrove plants were collected, identified and aqueous extracts screened for their protective effect on the giant tiger shrimp Penaeus monodon against WSSV. The experimental design consisted two modes of application, such as exposure of the virus to the extract and injection challenge, and oral administration of the extract coated feed followed by oral challenge. All experimental animals were monitored through a nested diagnostic PCR analysis. Of the seven mangrove extracts screened aqueous extract from Ceriops tagal imparted total protection to shrimp from WSSV when challenged by both methods. Shrimps administered with the aqueous extract from C. tagal were devoid of virions. The HPLC fingerprint of the aqueous extracts from C. tagal showed more than 25 peaks and 7 of them were larger and well separated. Preliminary phytochemical analysis revealed the presence of alkaloids, flavonoids, polyphenolics, cardiac glycosides, saponins and sterols. The study indicated suitability of the aqueous extract of C. tagal as a possible prophylaxis for WSSV infection in shrimp. This is the first report on the anti WSSV property of the mangrove plant C. tagal