scholarly journals Design of low- area, power fault tolerant parallel FFTs using trellis codes

2018 ◽  
Vol 7 (4) ◽  
pp. 2338
Author(s):  
B. NagaSaiLakshmi ◽  
RajaSekhar. T
Keyword(s):  
Error Correction ◽  
Fault Tolerant ◽  
Error Correction Codes ◽  
Electronic Circuits ◽  
Trellis Codes ◽  
Low Area ◽  
Trellis Code ◽  
Synthesis Report ◽  
Parallel Fft ◽  
Algorithmic Based Fault Tolerance

Present day electronic circuits are generally affected by the delicate mistakes. To maintain the reliability of the complex systems few techniques have been proposed. For few applications, an algorithmic - based fault tolerance (ABFT) system has attempt to abuse the algorithmic properties to identify and adjust mistakes. One example FFT used. There are various protection schemes to identify and adjust errors in FFTs. It is normal to discover various blocks are working in parallel. Recently; a new method is exploiting to implement a blame tolerance in parallel. In this work, same method is first applicable to parallel FFT and then secured methods are merged that the use of error correction codes (ECCs) and parseval checks are used to detect and correct a single bit fault. Trellis code is applied to parallel FFTs to protect the errors which are used to detect and correct a multibit faults are proposed and evaluated. The 4-point FFT is protected with the input32-bit length .Simulation and Synthesis report for FFT using ECC,SOS,ECC-SOS,Trellis codes are obtained in Xilinx software14.2v.Area,power,delay is analyzed in cadence using 90nm & 180nmTechnology. 

scholarly journals Theory of quasi-exact fault-tolerant quantum computing and valence-bond-solid codes

2021 ◽  
Author(s):  
Dongsheng Wang ◽  
Yunjiang Wang ◽  
Ningping Cao ◽  
Bei Zeng ◽  
Raymond Lafflamme
Keyword(s):  
Error Correction ◽  
Quantum Computation ◽  
Fault Tolerant ◽  
Valence Bond ◽  
Quantum Error Correction ◽  
Quantum Codes ◽  
Error Correction Codes ◽  
Exact Quantum ◽  
Valence Bond Solid ◽  
Quantum Error

Abstract In this work, we develop the theory of quasi-exact fault-tolerant quantum (QEQ) computation, which uses qubits encoded into quasi-exact quantum error-correction codes (``quasi codes''). By definition, a quasi code is a parametric approximate code that can become exact by tuning its parameters. The model of QEQ computation lies in between the two well-known ones: the usual noisy quantum computation without error correction and the usual fault-tolerant quantum computation, but closer to the later. Many notions of exact quantum codes need to be adjusted for the quasi setting. Here we develop quasi error-correction theory using quantum instrument, the notions of quasi universality, quasi code distances, and quasi thresholds, etc. We find a wide class of quasi codes which are called valence-bond-solid codes, and we use them as concrete examples to demonstrate QEQ computation.

Fault Tolerant Parallel Filters Based on Error Correction Codes

2015 ◽  
Vol 23 (2) ◽  
pp. 384-387 ◽  
Author(s):  
Zhen Gao ◽  
Pedro Reviriego ◽  
Wen Pan ◽  
Zhan Xu ◽  
Ming Zhao ◽  
...  
Keyword(s):  
Error Correction ◽  
Fault Tolerant ◽  
Error Correction Codes

scholarly journals Dynamic VlSI Methods for OLSE and Syndrome Calculation using Synchronized Mitigation Procedures for Intact Circuit Functionality

2019 ◽  
Vol 8 (2S4) ◽  
pp. 383-386
Keyword(s):  
Error Correction ◽  
Research Work ◽  
Vlsi Design ◽  
Error Correction Codes ◽  
Electronic Circuits ◽  
Verilog Hdl ◽  
Suggested Technique ◽  
Major Parameter ◽  
Decoder Circuit

Now a days in VLSI design circuit’s reliability has become the major parameter of concern. With the consistently expanding requests for higher speed and lower control correspondence frameworks, productive VLSI executions of those blunder redress codes have extraordinary significance for reasonable applications. There exists various synchronized moderation procedures proposed to ensure that the blunders don't influence the circuit usefulness. Among them, to ensure the recollections and registers in electronic circuits Error Correction Codes (ECC) is normally utilized. At whatever point any ECC method is utilized, the encoder and decoder circuit may likewise endure mistakes. Here synchronized slip identification Also revision method to OLS encoders (OLSE) What's more syndrome figuring is suggested What's more assessed. Those suggested technique proficiently executes An equality prediction plan that detects the greater part errors that influence An solitary out hub utilizing the properties of OLS codes. Today VLSI design means usage of Verilog or VHDL. In this research work Verilog HDL is used for simulation and Synplify for synthesis purpose.

Fault Tolerant Parallel FFTs Using Error Correction Codes and Parseval Checks

2016 ◽  
Vol 24 (2) ◽  
pp. 769-773 ◽  
Author(s):  
Zhen Gao ◽  
Pedro Reviriego ◽  
Zhan Xu ◽  
Xin Su ◽  
Ming Zhao ◽  
...  
Keyword(s):  
Error Correction ◽  
Fault Tolerant ◽  
Error Correction Codes

Fault tolerant encoders for Single Error Correction and Double Adjacent Error Correction codes

2018 ◽  
Vol 81 ◽  
pp. 167-173 ◽  
Author(s):  
Shanshan Liu ◽  
Pedro Reviriego ◽  
Juan Antonio Maestro ◽  
Liyi Xiao
Keyword(s):  
Error Correction ◽  
Fault Tolerant ◽  
Error Correction Codes ◽  
Single Error

scholarly journals Optimizing Quantum Error Correction Codes with Reinforcement Learning

Quantum ◽  
2019 ◽  
Vol 3 ◽  
pp. 215 ◽  
Author(s):  
Hendrik Poulsen Nautrup ◽  
Nicolas Delfosse ◽  
Vedran Dunjko ◽  
Hans J. Briegel ◽  
Nicolai Friis
Keyword(s):  
Reinforcement Learning ◽  
Error Correction ◽  
Fault Tolerant ◽  
Quantum Error Correction ◽  
Error Correction Codes ◽  
Learning Agent ◽  
On Line ◽  
Quantum Error Correction Codes ◽  
Surface Code ◽  
Quantum Error

Quantum error correction is widely thought to be the key to fault-tolerant quantum computation. However, determining the most suited encoding for unknown error channels or specific laboratory setups is highly challenging. Here, we present a reinforcement learning framework for optimizing and fault-tolerantly adapting quantum error correction codes. We consider a reinforcement learning agent tasked with modifying a family of surface code quantum memories until a desired logical error rate is reached. Using efficient simulations with about 70 data qubits with arbitrary connectivity, we demonstrate that such a reinforcement learning agent can determine near-optimal solutions, in terms of the number of data qubits, for various error models of interest. Moreover, we show that agents trained on one setting are able to successfully transfer their experience to different settings. This ability for transfer learning showcases the inherent strengths of reinforcement learning and the applicability of our approach for optimization from off-line simulations to on-line laboratory settings.

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