Abstract-This paper describes our work toward the development of a computationally robust methodology to identify the pyloric neurons in the stomatogastric ganglion of Cancer pagurus using voltage-sensitive dye imaging. The multi-resolution signal decomposition procedure constructed using the sequential Singular Spectrum Analysis approach to isolate the pyloric rhythm from optical recordings of dyed live cells is presented. Early results suggest that the developed procedure offers a demonstrably reliable way to extract the rhythm from the recording data of these cells.
GARCH model has a long history and permeates the modern financial theory. Most researchers use several thousands of financial data and maximum likelihood to estimate the coefficients of model. Statistically, more samples imply better estimation but are hard to obtain. How many samples are sufficient for estimation? What is the impact of the limited samples on the estimation? In this paper, we examined these questions using GARCH, MEM-GARCH models and NASDAQ composite index. The problems, raised from the limited samples, were discussed. Correlation of the conditional variances of the estimated models between the limited samples and the large samples were calculated. The effectiveness of model estimation for the limited samples was evaluated by the correlation.
Abstract. Voltage-sensitive dye imaging (VSDi) which enables simultaneous optical recording of many neurons in the pyloric circuit of the stomatogastric ganglion is an important technique to supplement electrophysiological recordings. However, utilising the technique to identify pyloric neurons directly is a computationally exacting task that requires the development of sophisticated signal processing procedures to analyse the tri-phasic pyloric patterns generated by these neurons. This paper presents our work towards commissioning such procedures. The results achieved to date are most encouraging. .
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