This paper introduces a machine learning based collaborative multi-band spectrum sensing policy for cognitive radios. The proposed sensing policy guides secondary users to focus the search of unused radio spectrum to those frequencies that persistently provide them high data rate. The proposed policy is based on machine learning, which makes it adaptive with the temporally and spatially varying...

Lam (2007) introduces a generalization of renewal processes named Geometric processes, where inter-arrival times are independent and identically distributed up to a multiplicative scale parameter, in a geometric fashion. We here envision a more general scaling, not necessar- ily geometric. The corresponding counting process is named Extended Geometric Process (EGP). Semiparametric estimates are...

In this article, two different systems subject to shocks occurring based on a non-homogeneous Poisson process (NHPP) are analyzed. Type –I system is consisted of a single unit and type –II system is consisted of two parallel units in which both units operate identically and simultaneously. In type –I system occurrence of a shock causes system stopping and consequently will be received minimal r...

Replacement policies for cache management have been studied extensively. Most policies proposed in the literature tend to be ad hoc and typically exploit the retrieval cost or latency of the objects, object sizes, popularity of requests and temporal correlations between requests. A recent paper [1] studied the caching problem and developed an optimal replacement policy C ∗ 0 under the independe...

Due to the huge difference in performance between the computer memory and processor , the virtual memory management plays a vital role in system performance .A Cache memory is the fast memory which is used to compensate the speed difference between the memory and processor. This paper gives an adaptive replacement policy over the traditional policy which has low overhead, better performance and...

We study an inspection and replacement policy for a system when maintenance actions are executed at times or “visits” with fixed, periodic schedule. Then, the novel focus of paper is not to schedule but what known times. Violations (defaults) may occur because time resource limited. The model motivated by typically used high-value, engineered systems e.g. windfarms, transportation systems, manu...

Stochastic gradient methods for machine learning and optimization problems are usually analyzed assuming data points are sampled with replacement. In practice, however, sampling without replacement is very common, easier to implement in many cases, and often performs better. In this paper, we provide competitive convergence guarantees for without-replacement sampling, under various scenarios, f...