Abstract— In this paper differential space–frequency modulation (DSFM) for transmission over multiple–input multiple– output channels using orthogonal frequency division mu...
Many real datasets have uncertain categorical attribute values that are only approximately measured or imputed. Uncertainty in categorical data is commonplace in many applications...
— The need for efficient counter architecture has arisen for the following two reasons. Firstly, a number of data streaming algorithms and network management applications requir...
Markov decision processes (MDPs) are controllable discrete event systems with stochastic transitions. The payoff received by the controller can be evaluated in different ways, dep...
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...