Studies on the synthesis and cns activity of strychnine derivatives

Strychnine, the major alkaloid present in Strychnos nuxvomica seeds has been reported to stimulate the entire central nervous system with preference for the spinal cord. It is a powerful convulsant and because of this property, it is an important pharmacological tool as it plays a unique role as an inhibitor of post synaptic inhibitory impulses. It is useful to study inhibitory transmitter and receptor types. However, because of its extreme toxicity, strychnine does not have any therapeutic application in the Western system of medicine. The present work was undertaken with a view to obtaining strychnine derivatives having CNS stimulating properties but with sufficiently low toxicity so that they may eventually find some application in medicine. As strychnine is isolated from the locally available strychnos Nugvomica seeds, it’s possible utilization in therapeutics will have considerable commercial significance. This work tries to provide several new compounds which are significantly less toxic than strychnine and its N—oxide as shown from the pharmacological Studio As they also possessed CNS stimulating properties, they are well suited for further screening to assess their potential as valuable therapeutic agents.

Median filtering: structure analysis and application

Median filtering is a simple digital non—linear signal smoothing operation in which median of the samples in a sliding window replaces the sample at the middle of the window. The resulting filtered sequence tends to follow polynomial trends in the original sample sequence. Median filter preserves signal edges while filtering out impulses. Due to this property, median filtering is finding applications in many areas of image and speech processing. Though median filtering is simple to realise digitally, its properties are not easily analysed with standard analysis techniques,

Speaker identification using models for phonemes

Motivation for Speaker recognition work is presented in the first part of the thesis. An exhaustive survey of past work in this field is also presented. A low cost system not including complex computation has been chosen for implementation. Towards achieving this a PC based system is designed and developed. A front end analog to digital convertor (12 bit) is built and interfaced to a PC. Software to control the ADC and to perform various analytical functions including feature vector evaluation is developed. It is shown that a fixed set of phrases incorporating evenly balanced phonemes is aptly suited for the speaker recognition work at hand. A set of phrases are chosen for recognition. Two new methods are adopted for the feature evaluation. Some new measurements involving a symmetry check method for pitch period detection and ACE‘ are used as featured. Arguments are provided to show the need for a new model for speech production. Starting from heuristic, a knowledge based (KB) speech production model is presented. In this model, a KB provides impulses to a voice producing mechanism and constant correction is applied via a feedback path. It is this correction that differs from speaker to speaker. Methods of defining measurable parameters for use as features are described. Algorithms for speaker recognition are developed and implemented. Two methods are presented. The first is based on the model postulated. Here the entropy on the utterance of a phoneme is evaluated. The transitions of voiced regions are used as speaker dependent features. The second method presented uses features found in other works, but evaluated differently. A knock—out scheme is used to provide the weightage values for the selection of features. Results of implementation are presented which show on an average of 80% recognition. It is also shown that if there are long gaps between sessions, the performance deteriorates and is speaker dependent. Cross recognition percentages are also presented and this in the worst case rises to 30% while the best case is 0%. Suggestions for further work are given in the concluding chapter.