Results 11 to 20 of about 132 (124)

Weight distribution of turbo codes with convolutional interleavers

IET Communications, 2007
A simple algorithm for the weight calculation of turbo codes with convolutional interleavers is presented. For codes with short interleaver lengths, the weight distributions are computed using conventionally proposed methods and then utilised together with the interleaver properties to determine the weight specifications for the code with a longer ...
Vafi, S., Wysocki, T.
openaire   +3 more sources

Blind Interleaver Recognition Using Deep Learning Techniques

IEEE Access
In digital communication systems, channel encoders and interleavers play a crucial role in mitigating the random and burst errors introduced by noisy channels.
Nayim Ahamed, Swaminathan R., B. Naveen
doaj   +1 more source

Interleaved Group Convolutions for Deep Neural Networks

CoRR, 2017
To appear in ICCV ...
Ting Zhang 0002, Guo-Jun Qi, Bin Xiao 0001, Jingdong Wang 0001   +3 more
openaire   +2 more sources

New Code Matched Interleaver for Turbo Codes with Short Frames

Advances in Electrical and Computer Engineering, 2010
Turbo codes are a parallel concatenation of two or more convolutional codes, separated by interleavers, therefore their performance is not influenced just by the constituent encoders, but also by the interleaver.
LAZAR, G. A., BUZATU, N. R., COJOCARIU, E., TRIFINA, L.   +3 more
doaj   +1 more source

Blind identification of an unknown interleaved convolutional code [PDF]

2015 IEEE International Symposium on Information Theory (ISIT), 2015
We give here an efficient method to reconstruct the block interleaver and recover the convolutional code when several noisy interleaved codewords are given. We reconstruct the block interleaver without assumption on its structure. By running some experimental tests we show the efficiency of this method even with moderate noise.
openaire   +3 more sources

A Closed‐Loop Framework for Inverse Design: Dynamic Training and Intelligent Optimization for Heterostructured Materials

Advanced Science, EarlyView.
To accelerate the inverse design of heterostructured metal matrix composites, a closed‐loop scientific machine learning framework integrates continual learning prediction with NSGA‐II‐PMCP optimization. The framework maps microstructural descriptors to strength, toughness, and modulus, expands high‐quality Pareto solutions, and guides experimentally ...
Zhiyan Zhong, Xueru Zheng, Xiao Zhou, Zhengheng Tao, Wan Han, Jingyi Pan, Dian Wu, Ning Gao, Lei Liu, Zhongyang Wang, Fanchao Meng, Tongxiang Fan   +11 more
wiley   +1 more source

Interleaving Gains for Receive Diversity Schemes of Distributed Turbo Codes in Wireless Half–Duplex Relay Channels [PDF]

Radioengineering, 2015
This paper proposes the interleaving gain in two different distributed turbo-coding schemes: Distributed Turbo Codes (DTC) and Distributed Multiple Turbo Codes (DMTC) for half-duplex relay system as an extension of our previous work on turbo coding ...
Tamer H. M. Soliman, Fengfan Yang, S. Ejaz   +2 more
doaj  

Strategy of Triple‐Gradient in Binary Pixels for Flexible Pressure Sensing with High Sensitivity and Wide‐Range Linearity

Advanced Science, EarlyView.
A flexible pressure sensor with triple‐gradient design of conductivity, modulus, and dimension in binary micro‐dome pixels is proposed. Based on precisely‐designed CNT/PDMS matrix, the device exhibits a linear sensitivity of 974.1 kPa−1 across range up to 1.8 MPa (R2 > 0.99), offering an effective strategy for potential applications in healthcare ...
Yifan Liu, Xiao Xu, Fengming Hu, Yuanzhe Liang, Zidong Yin, Biao Qi, Ruolin Liu, Ziyi Dai, Jianyi Luo, Bingpu Zhou   +9 more
wiley   +1 more source

A Unified Flash Memory Platform for Mode‐Adaptive and Robust AI Computation

Advanced Science, EarlyView.
A unified AND‐type flash memory platform enables both transistor‐mode and capacitor‐mode computing‐in‐memory operations within the same device structure. By selectively switching the sensing mode through peripheral reconfiguration, the platform provides adaptable trade‐offs between computational accuracy, robustness, and energy efficiency for AI ...
Dayeon Yu, Hwiho Hwang, Byeongchan Oh, Junmo Lee, Shimeng Yu, Tae‐Hyeon Kim, Hyungjin Kim   +6 more
wiley   +1 more source

Gap‐Free Information Transfer in 4D‐STEM via Fusion of Complementary Scattering Channels

Advanced Science, EarlyView.
Fused Full‐Field STEM (FF‐STEM) is introduced as a 4D‐STEM imaging modality that combines direct ptychography with tilt‐corrected dark‐field reconstruction in a single acquisition. Fourier‐space fusion using Wiener‐type spectral weighting closes the low‐frequency contrast gap inherent to bright‐field methods, delivering gap‐free, dose‐efficient, near ...
Shengbo You, Georgios Varnavides, Sagar Khavnekar, Nikita Palatkin, Sihan Shao, Mingjian Wu, Daniel Stroppa, Darya Chernikova, Baixu Zhu, Ricardo Egoavil, Stefano Vespucci, Dileep Krishnan, Xingchen Ye, Florian K. M. Schur, Erdmann Spiecker, Philipp Pelz   +15 more
wiley   +1 more source