Abstract So far, multiple classifier systems have been increasingly designed to take advantage of hardware features, such as high parallelism and computational power. Indeed, compared software implementations, accelerators guarantee higher throughput lower latency. Although the combination classifiers leads classification accuracy, required area overhead makes design a accelerator unfeasible, h...

In this work, approximate formulas are presented for computing the magnetic field intensity near electric power transmission lines. Original expressions are given for single circuit lines of any type of arrangement and double circuit lines in both super-bundle and low-reactance conductor phasing. These expressions can be used for assessing directly the Right-of-Way width of power lines related ...

The approximate logarithmic multiplier proposed by Mitchell provides an efficient alternative for processing dense multiplication or multiply-accumulate operations in applications such as image and real-time robotics. It offers the advantages of small area, high energy efficiency is suitable that do not necessarily achieve accuracy. However, its maximum error 11.1% makes it challenging to deplo...

Successful algorithms have been developed for computing Nash equilibrium in a variety of finite game classes. However, solving continuous games—in which the pure strategy space is (potentially uncountably) infinite—is far more challenging. Nonetheless, many real-world domains action spaces, e.g., where actions refer to an amount time, money, or other resource that naturally modeled as being rea...

Quantum approximate optimization algorithms can efficiently initialize the ground states of two-dimensional lattice gauge theory in different phases, showing signatures topological order systems sizes comparable to modern quantum computing platforms.

There are several numerical methods for computing approximate zeros of a given univariate polynomial. In this paper, we develop a simple and novel method for determining sharp upper bounds on errors in approximate zeros of a given polynomial using Rouche's theorem from complex analysis. We compute the error bounds using non-linear optimization. Our bounds are scalable in the sense that we compu...

Trading small amounts of output accuracy to obtain significant performance improvement or reduce power consumption is a promising research direction. Many modern applications from different domains such as image and signal processing, computer vision, data mining, machine learning and speech recognition are amenable to approximate computing. In many cases, their output is interpreted by humans,...