Browsing by Subject "Monte Carlo Simulation"

Now showing 1 - 3 of 3

Open Access
Model-based spectral analysis of photon propagation through nanoparticle-labeled epithelial tissues
(SPIE, 2011) Cihan, Can; Arifler, D.
Metal nanoparticles can function as optical contrast enhancers for reflectance-based diagnosis of epithelial precancer. We carry out Monte Carlo simulations to model photon propagation through normal tissues, unlabeled precancerous tissues, and precancerous tissues labeled with gold nanospheres and we compute the spectral reflectance response of these different tissue states. The results indicate that nanoparticle-induced changes in the spectral reflectance profile of tissues depend not only on the properties of these particles but also on the source-detector geometry used. When the source and detector fibers are oriented side by side and perpendicular to the tissue surface, the reflectance intensity of precancerous tissue is lower compared to that of normal tissue over the entire wavelength range simulated and addition of nanospheres enhances this negative contrast. When the fibers are tilted toward each other, the reflectance intensity of precancerous tissue is higher compared to that of normal tissue and labeling with nanospheres causes a significant enhancement of this positive contrast. The results also suggest that model-based spectral analysis of photon propagation through nanoparticle-labeled tissues provides a useful framework to quantify the extent of achievable contrast enhancement due to external labeling and to assess the diagnostic potential of nanoparticle-enhanced optical measurements. © 2011 SPIE-OSA.
Open Access
Successive cancelation approach for doppler frequency estimation in pulse doppler radar systems
(IEEE, 2010) Soğancı, Hamza; Gezici, Sinan
In this paper, a successive cancelation approach is proposed to estimate Doppler frequencies of targets in pulse Doppler radar systems. This technique utilizes the Doppler domain waveform structure of the received signal coming from a point target after matched filtering and pulse Doppler processing steps. The proposed technique is an iterative algorithm. In each iteration, a target that minimizes a cost function is found, and the signal coming from that target is subtracted from the total received signal. These steps are repeated until there are no more targets. The global minimum value of the cost function in each iteration is found via particle swarm optimization (PSO). Performance of this technique is compared with the optimal maximum likelihood solution for various signal-to-noise ratio (SNR) values based on Monte Carlo simulations.
Open Access
A test of independence in two-way contingency tables based on maximal correlation
(Taylor & Francis, 2011) Yenigün, C. D.; Székely, G. J.; Rizzo, M. L.
Maximal correlation has several desirable properties as a measure of dependence, including the fact that it vanishes if and only if the variables are independent. Except for a few special cases, it is hard to evaluate maximal correlation explicitly. We focus on two-dimensional contingency tables and discuss a procedure for estimating maximal correlation, which we use for constructing a test of independence. We compare the maximal correlation test with other tests of independence by Monte Carlo simulations. When the underlying continuous variables are dependent but uncorrelated, we point out some cases for which the new test is more powerful.