Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 19 of 19 for “"binary hypothesis testing"”.
-
Data selection in binary hypothesis testing
… algorithms for data selection combined with binary hypothesis testing. We develop models for data selection in several cases, considering both random and deterministic approaches. Our considerations are divided into two classes depending upon the amount of information available about the …
-
Binary classification with training under both classes
This thesis focuses on the binary classification problem with training data under both classes. We first review binary hypothesis testing problems and present a new result on the case of countably infinite alphabet. The goal of binary hypothesis testing is to decide between the two underlying …
-
Information-theoretic analysis of human-machine mixed systems
… also investigate social learning as sequential binary hypothesis testing. We find somewhat counterintuitively that unlike basic binary hypothesis testing, the decision threshold determined by the true prior probability is no longer optimal and biased perception of the true prior could outperform …
-
Acoustic and seismic signal processing for footsetp detection
… prediction coefficients leads to the classical binary hypothesis testing framework. Lastly, a new method for blindly estimating the filters of a SIMO channel is presented. This method is attractive because it allows for a more tractable performance analysis.
-
Quantum State Discrimination with Overcompleteness
… of this thesis are operating characteristics for binary hypothesis testing in classical and quantum settings and overcomplete quantum measurements for quantum binary state discrimination. With this we explore decision and measurement operating characteristics defined as the tradeoff between …
-
Monitoring unknown source IP addresses and packet sizes to detect DDoS attacks
… model is formulated as a xed sample size binary hypothesis testing. The decision making is based on the Neyman-Pearson criteria. The second parametric model is a sequential probability ratio test where the sample size is a random variable. Acceptance and rejection boundaries are deduced …
-
PacGAN: The power of two samples in generative adversarial networks
… generated. We borrow analysis tools from binary hypothesis testing---in particular the seminal result of Blackwell \cite{Bla53}---to prove a fundamental connection between packing and mode collapse. We show that packing naturally penalizes generators with mode collapse, thereby favoring …
-
SEQUENTIAL METHODS FOR NON-PARAMETRIC HYPOTHESIS TESTING
… develop such algorithms for two-sided sequential binary hypothesis testing.</p> <p>In this dissertation, we propose two algorithms for sequential non-parametric hypothesis testing. The proposed algorithms are based on the random distortion testing (RDT) framework. The RDT framework addresses the …
-
On the Design and Analysis of Secure Inference Networks
… two types of statistical inference, namely binary-hypothesis testing and scalar parameter estimation in parallel-topology inference networks. We address three different types of security threats in parallel-topology inference networks, namely Eavesdropping (Data-Confidentiality), Byzantine …
-
Spectrum sensing, spectrum monitoring, and security in cognitive radios
… We also consider the problem of centralized binary hypothesis testing in a cognitive radio network (CRN) consisting of multiple classes of cognitive radios, where the cognitive radios are classified according to the probability density function (PDF) of their received data (at the FC) under …
-
Decision-Making with Heterogeneous Sensors - A Copula Based Approach
… is addressed, especially in the context of binary hypothesis testing problems. Both, the training-testing paradigm, where a training set is assumed to be available for learning the copula models prior to system deployment, as well as generalized likelihood ratio test (GLRT) based fusion rule …
-
Statistical Hypothesis Testing Under Model Uncertainty
Statistical testing is one of the main problems in statistics and finds applications in a number of fields, including engineering, signal processing, medicine, and finance among others. Traditionally in hypothesis testing problem, the hypothesis distributions subject to testing are known. However, …
-
Extracting classical information from quantum states : fundamental limits, adaptive and finite-length measurements
… on the previous observations. We show that for binary hypothesis testing between two ideal laser light pulses, if we update the adaptive measurement to maximize the communication efficiency at each instant, based on recursively updated knowledge of the receiver, then we can achieve the …
-
Bayesian Estimators, Error Bounds, and Applications to Imaging
… via the minimum probability of error (MPE) of a binary hypothesis testing problem. Extensions of the Ziv-Zakai lower bound and some computationally efficient approximations are derived. The extensions include a bound in terms of the MPE of an M-ary hypothesis testing problem and another bound for …
-
Locally Adaptive Protocols for Quantum State Discrimination
… effective for the task of multiple quantum hypothesis testing. </p><p>Quantum hypothesis testing consists of finding the quantum measurement which allows one to discriminate with minimal error between $m$ possible states $\{\rho_{k}\}|_{k=1}^{m}$ of a quantum system with corresponding prior …
-
Augmented Human Machine Intelligence for Distributed Inference
… making and derive human decision rules in binary decision making. We model the decision-making by generic humans working in complex networked environments that feature uncertainties, and develop new approaches and frameworks facilitating collaborative human decision making and cognitive …
-
Detection of sparse mixtures: fundamental limits and algorithms
… study the sparse mixture detection problem as a binary hypothesis testing problem. Under the null hypothesis, we observe i.i.d. samples from a known noise distribution. Under the alternative hypothesis, we observe i.i.d. samples from a mixture of the noise distribution and signal distribution. …
-
Ambient Backscatter Communication Systems: Design, Signal Detection and Bit Error Rate Analysis
… non-central chi-squared random variable for the binary hypothesis testing problem is first handled in our study, which is a key contribution of this particular work. The evaluation of the maximum likelihood (ML) detection threshold is also explored which is found to be intractable. To overcome …
-
Channel parameter tuning in a hybrid Wi-Fi-Dynamic Spectrum Access Wireless Mesh Network
… of Secondary User (SU)-SU coexistence than the binary hypothesis testing methods that are most common in the literature. Furthermore, we construct confidence intervals based on the probability density function derived for the observations. This leads to finding and showing the relationships …