In this paper an optimal finite bit representation of Pi is presented. The goal is to completely nullify the possibility of error arising due to finite bit Pi representation while converting angle from degree (fixed point) to radian (IEEE 754 Single Precision floating point). Such a conversion is widely used in FPGA based interfacing device for military and aerospace applications, where there is minimal tolerance for error in the system. Through CAD based approach it is determined that atleast 40 bits are required to represent Pi while converting angle from 16 bit degree in 2's complement to IEEE 754 Single Precision floating point radian.
Spintronics has emerged now as a viable post CMOS technology. The main goal of this paper is to demonstrate pattern recognition using a cluster of eight Spin Transfer Torque (STT) devices biased to operate as variable frequency oscillators, Spin Torque Nano Oscillators (STNO).The phases of STNOs can be correlated to detect a trained input pattern. This is further used to design a correlator that detects the similarity of two patterns. While the spintronics devices are generally optimized for storing binary digital data, this paper shows how they can be configured to execute neuromorphic tasks without requiring any neurons and synaptic elements.
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