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Stochastic computing using simple logic circuits requires significantly less area and consumes less power compared to traditional computing systems. These circuits are also inherently fault-tolerant. The main drawbacks of these systems include long latency and inexactness in computing. The deviation from exact values increases as the correlation among inputs increases. In many applications, outputs...
This paper addresses implementations of tangent hyperbolic and sigmoid functions using stochastic logic. Stochastic computing requires simple logic gates and is inherently fault-tolerant. Thus, these structures are well suited for nanoscale CMOS technologies. Tangent hyperbolic and sigmoid functions are widely used in machine learning systems such as neural networks. This paper makes two major contributions...
This work presents improved implementations of memristor-based ripple carry adders using three different approaches: the IMPLY operation, hybrid-CMOS gates, and threshold gates. The designs are optimized by performing parallel operations, leveraging computational redundancies, and recognizing Boolean simplifications. The proposed IMPLY N-bit ripple carry adder decreases the area by 2N-1 components...
A novel approach to design capacity-approaching variable-length constrained sequence codes has recently been developed. A critical step in this design process is the construction of minimal sets based on a finite state machine description of the encoders. In this paper we propose three generalized criteria to select the state that will result in construction of the minimal set with the best achievable...
In this paper, decentralized change point detection problem with optional observations at the fusion center is considered. In the model considered, there are two sensors: a peripheral sensor and a coordinating sensor. At each time, the peripheral sensor decides whether to stop and send an alarm to the coordinating sensor or to continue making observations. Once the coordinating sensor receives an...
Approximate computing offers pathways to increased energy efficiency in computational settings where perfect accuracy is not required. In this work, we explore fundamental links between approximation, information loss, and limiting energy efficiency of computation. We distinguish physical and semantic aspects of approximation in digital computation, and show how the physical aspects — whether of deterministic...
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