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Spectrum Sharing And Service Pricing In Dynamic Spectrum Access Networks, Swastik Kumar Brahma
Spectrum Sharing And Service Pricing In Dynamic Spectrum Access Networks, Swastik Kumar Brahma
Electronic Theses and Dissertations
Traditionally, radio spectrum has been statically allocated to wireless service providers (WSPs). Regulators, like FCC, give wireless service providers exclusive long term licenses for using specific range of frequencies in particular geographic areas. Moreover, restrictions are imposed on the technologies to be used and the services to be provided. The lack of flexibility in static spectrum allocation constrains the ability to make use of new technologies and the ability to redeploy the spectrum to higher valued uses, thereby resulting in inefficient spectrum utilization [23, 38, 42, 62, 67]. These limitations have motivated a paradigm shift from static spectrum allocation towards …
Global Secure Sets Of Trees And Grid-Like Graphs, Yiu Yu Ho
Global Secure Sets Of Trees And Grid-Like Graphs, Yiu Yu Ho
Electronic Theses and Dissertations
Let G = (V, E) be a graph and let S ⊆ V be a subset of vertices. The set S is a defensive alliance if for all x ∈ S, |N[x] ∩ S| ≥ |N[x] − S|. The concept of defensive alliances was introduced in [KHH04], primarily for the modeling of nations in times of war, where allied nations are in mutual agreement to join forces if any one of them is attacked. For a vertex x in a defensive alliance, the number of neighbors of x inside the alliance, plus the vertex x, is at least the number …
Convergence Of The Mean Shift Algorithm And Its Generalizations, Ting Hu
Convergence Of The Mean Shift Algorithm And Its Generalizations, Ting Hu
Electronic Theses and Dissertations
Mean shift is an effective iterative algorithm widely used in image analysis tasks like tracking, image segmentation, smoothing, filtering, edge detection and etc. It iteratively estimates the modes of the probability function of a set of sample data points based in a region. Mean shift was invented in 1975, but it was not widely used until the work by Cheng in 1995. After that, it becomes popular in computer vision. However the convergence, a key character of any iterative algorithm, has been rigorously proved only very recently, but with strong assumptions. In this thesis, the method of mean shift is …
Labeled Sampling Consensus A Novel Algorithm For Robustly Fitting Multiple Structures Using Compressed Sampling, Carl J. Messina
Labeled Sampling Consensus A Novel Algorithm For Robustly Fitting Multiple Structures Using Compressed Sampling, Carl J. Messina
Electronic Theses and Dissertations
The ability to robustly fit structures in datasets that contain outliers is a very important task in Image Processing, Pattern Recognition and Computer Vision. Random Sampling Consensus or RANSAC is a very popular method for this task, due to its ability to handle over 50% outliers. The problem with RANSAC is that it is only capable of finding a single structure. Therefore, if a dataset contains multiple structures, they must be found sequentially by finding the best fit, removing the points, and repeating the process. However, removing incorrect points from the dataset could prove disastrous. This thesis offers a novel …