One of the fast multiplication methods is Karartsuba gorithm. The polynomial edition of extensively studied for efficient realization. These studies try to improve the and cost in both algorithm and device level. However, the question to answer is: does reducing the complexity necessarily results in faster or cheaper hardware?

In this work, we show that this not always the case for the Karatsuba algorithm.

Point-of-care (POC) platforms are getting more and more attraction, owing to their inexpensive, fast, and easy to use nature. An ideal POC platform can take volumes of chemical and biological samples, process them to detect desired target elements, without the need to have professionally trained users . In this research new techniques for capacitance for such sensors are under development.

Digital hardware-efficient approximation of the Izhikevich Spiking Neuron Model has been designed and implemented are under investigation. The result achieved through the development of this neuron is a hardware model that is an approximated version of the above-mentioned model which translates to simple digital circuitry. The efficiencies achieved in the model include a significant reduction in the number of multiplications necessary for modeling spiking phenomena, a reduction of the number of required output bits, and a reduction of the number of input parameters from four to one. All of these efficiencies significantly reduces the model size and cost.