منابع مشابه
Fault detection in complex analog circuits using Support Vector Machines
The aim of this paper is to bring the reader closer to the diagnostics of complex analog systems with parametric faults, using Support Vector Machine (SVM) as a tool for fault location. The results of diagnostics of a video enhancer and two low-pass filters with the help of SVM network are presented, and various SVM kernel functions tested. A strategy for finding the optimal kernels and their p...
متن کاملModeling Memory Errors in Pipelined Analog-to-digital Converters
Switched-capacitor implementations of pipelined ADCs contain several sources of memory errors, including capacitor dielectric absorption/relaxation, incomplete stage reset at high clock rates, and parasitic capacitance effects when op amps are shared between subsequent pipeline stages. This paper describes these sources of memory errors and presents a unified model for their effect. The depende...
متن کاملPerformance evaluation of coherent Ising machines against classical neural networks
The coherent Isingmachine is expected tofind a near-optimal solution in various combinatorial optimization problems, which has been experimentally confirmedwith optical parametric oscillators and afield programmable gate array circuit. The similarmathematicalmodels were proposed three decades ago byHopfield et al in the context of classical neural networks. In this article, we compare the compu...
متن کاملOn mismatch errors in analog-VLSI error correcting decoders
A new type of nonlinear analog transistor networks has recently been proposed for “turbo” decoding of error correcting codes. However, the influence of various nonidealities on the performance of such analog decoders is not yet well understood. The paper addresses the performance degradation due to transistor mismatch. Some analytical results are derived that allow to compare the accuracy of an...
متن کاملDetecting Errors in Corpora Using Support Vector Machines
While the corpus-based research relies on human annotated corpora, it is often said that a non-negligible amount of errors remain even in frequently used corpora such as Penn Treebank. Detection of errors in annotated corpora is important for corpus-based natural language processing. In this paper, we propose a method to detect errors in corpora using support vector machines (SVMs). This method...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Quantum Science and Technology
سال: 2019
ISSN: 2058-9565
DOI: 10.1088/2058-9565/ab13ea