The group testing problem is concerned with identifying a small set of infected individuals in large population. At our disposal procedure that allows us to test several together. In an idealized setting, positive if and only at least one individual included negative otherwise. Significant progress was made recent years towards understanding the information-theoretic algorithmic properties this...

We consider Bayesian multiple statistical classification problem in the case where unknown source distributions are estimated from labeled training sequences, then estimates used as nominal a robust hypothesis test. Specifically, we employ DGL test due to Devroye et al. and provide non-asymptotic, exponential upper bounds on error probability of classification. The proposed simple evaluate reve...

The subject of this thesis is learning and testing properties of mixed quantum states. A mixed state is described by a density matrix ρ ∈ Cd×d. In the standard model, one is given access to many identical copies of the mixed state, and the goal is to perform measurements on the copies to infer some information about ρ. In our problem, each copy of ρ plays a role analogous to a sample drawn from...

T his study investigates the factors affecting the demand for new residential buildings in urban areas of Iran during 1976-2010. The demand function for new residential buildings in urban areas was estimated and then the existence of a long-run relationship among variables of this function was studied using the Bounds testing of the Autoregressive Distributed Lag Co-integration procedure. The t...

we give sharp upper bounds on the zagreb indices and lower bounds on the zagreb coindices of chemical trees and characterize the case of equality for each of these topological invariants.

Studies have shown that random testing can be an effective testing strategy. One of tbe goals of testing is to estimate the reliability of tbe program from tbe test outcomes. In tbis paper we extend tbe Tbayer-Lipow-Nelson reliability model to account for tbe cost of errors. Also we compare random with partition testing by looking at upper confidence bounds for the cost weighted performance of ...