Showing 2 results for H. Miar-Naimi
H. Miar-Naimi, P. Davari,
Volume 4, Issue 1 (April 2008)
Abstract
In this paper, a new Hidden Markov Model (HMM)-based face recognition
system is proposed. As a novel point despite of five-state HMM used in pervious
researches, we used 7-state HMM to cover more details. Indeed we add two new face
regions, eyebrows and chin, to the model. As another novel point, we used a small number
of quantized Singular Values Decomposition (SVD) coefficients as features describing
blocks of face images. This makes the system very fast. The system has been evaluated on
the Olivetti Research Laboratory (ORL) face database. In order to additional reduction in
computational complexity and memory consumption the images are resized to 64×64 jpeg
format. Before anything, an order-statistic filter is used as a preprocessing operation. Then
a top-down sequence of overlapping sub-image blocks is considered. Using quantized SVD
coefficients of these blocks, each face is considered as a numerical sequence that can be
easily modeled by HMM. The system has been examined on 400 face images of the Olivetti
Research Laboratory (ORL) face database. The experiments showed a recognition rate of
99%, using half of the images for training. The system has been evaluated on 64×64 jpeg
resized YALE database too. This database contains 165 face images with 231×195 pgm
format. Using five training image, we obtained 97.78% recognition rate where for six
training images the recognition rate was 100%, a record in the literature. The proposed
method is compared with the best researches in the literature. The results show that the
proposed method is the fastest one, having approximately 100% recognition rate.
P. M. Farahabadi, H. Miar-Naimi, A. Ebrahimzadeh,
Volume 5, Issue 1 (March 2009)
Abstract
New equations are proposed for frequency and amplitude of a ring oscillator.
The method is general enough to be used for all types of delay stages. Using exact largesignal
circuit analysis, closed form equations for estimating the frequency and amplitude of
a high frequency ring oscillator are derived as an example. The method takes into account
the effect of various parasitic capacitors to have better accuracy. Based on the loop gain of
the ring, the transistors may only be in saturation or experience cutoff and triode regions.
The analysis considers all of the above mentioned scenarios respectively and gives distinct
equations. The validity of the resulted equations is verified through simulations using
TSMC 0.18 µm CMOS process. Simulation results show the better accuracy of the
proposed method compared with others.
