This work is a survey on approximate computing and its impact on fault tolerance, especially
for safety-critical applications. It presents a multitude of approximation methodologies, which …

Approximate Computing (AxC) is a well-known paradigm able to reduce the computational
and power overheads of a multitude of applications, at the cost of a decreased accuracy …

Stochastic computing (SC) has become a promising approximate computing solution by its
negligible resource occupancy and ultralow energy consumption. As a potential …

Radio telescopes produce large volumes of data that need to be processed to obtain high-
resolution sky images. This is a complex task that requires computing systems that provide …

Solutions based on artificial intelligence and brain-inspired computations like Artificial
Neural Networks (ANNs) are suited to deal with the growing computational complexity …

The physical limits being reached in silicon-based computing, new ways have to be found to
overcome the predicted end of Moore's law. Many applications can tolerate approximations …

Using Spatial Domain Correlation Pattern Recognition (CPR) in Internet-of-Things (IoT)-
based applications often faces constraints, like inadequate computational resources and …

Now a day's various real time applications and image processing applications requires
hardware that can perform various complex arithmetic operations. These operations can be …

This chapter introduces the approximate computing paradigm and its implementation in the
various computing stack levels. Approximate computing can be applied to many different …

The thesis deals with numerical problems of sine wave fitting algorithms that are realized
with floating-point arithmetic. Sine wave fitting algorithms are applied in several fields of the …