Title :
A novel technique for PDF estimation using DSP methods
Author :
Kaushik, Akhil ; Parthasarathy, Harish ; Sengar, Prateek Singh
Author_Institution :
Div. of Electron. & Commun., Univ. of Delhi, New Delhi, India
Abstract :
This paper deals with estimating the pdf and joint pdf of a scalar and vector valued random variable using multirate signal processing methods. We estimate the pdf using a histogram and smoothen it out by passing the histogram through a multirate system comprising of a low pass filter and decimator. Such a multirate processing reduces variance of the histogram and can be readily generalized to the vector case i.e. the joint pdf. The low pass filter is designed to remove the high frequency components in the characteristic function of the histogram and hence smoothen it out. After passing through the decimator, we interpolate and use a low pass filter to remove the replicas generated. This low pass filter is the biorthogonal partner of earlier filter. The combination of (low pass filter1→ decimator) and (interpolator → low pass filter2) is chosen so that the output is minimum mean square estimate of the original sampled pdf. The combination of (low pass filter1→ decimator) and (interpolator → low pass filter2) is a linear time varying system and the design can be carried out using the standard orthogonal projection theory. The condition of biorthogonal partner guarantees unbiasedness of the pdf estimate.
Keywords :
estimation theory; interpolation; low-pass filters; mean square error methods; probability; random processes; signal processing; DSP methods; PDF estimation; biorthogonal partner; decimator; histogram variance; interpolation; linear time varying system; low pass filter; minimum mean square estimate; multirate processing; multirate signal processing methods; multirate system; probability density function estimation; scalar valued random variable; standard orthogonal projection theory; vector valued random variable; biorthogonal partner; multirate processing; probability density function; probability density function estimation;
Conference_Titel :
Signal Processing and Integrated Networks (SPIN), 2014 International Conference on
Conference_Location :
Noida
Print_ISBN :
978-1-4799-2865-1
DOI :
10.1109/SPIN.2014.6776919