Results 41 to 50 of about 8,087 (250)
THE EFFECT OF TRELLIS TERMINATION ON THE PERFORMANCE OF TURBO CODE
This paper introduces a new class of convolutional codes, which is called Turbo Code. Turbo Code was shown to achieve performance in terms of Bit-Error-Rate (BER), which is near Shannon limit.
H.H. Abbas, W. A. Mahmoud, S.K. Omran
doaj +1 more source
Data‐Driven Materials Science for Energy‐Sustainable Applications
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley +1 more source
A physics‐informed generative framework introduces Directional Latent Hybridization (DLH) for the deterministic inverse design of nonlinear metamaterials. By hybridizing dominant traits from parent geometries in the latent space, DLH overcomes the instabilities of stochastic models to ensure high structural precision at high densities.
Semin Ahn +2 more
wiley +1 more source
The error mechanisms of iterative message-passing decoders for low-density parity-check codes are studied. A tutorial review is given of the various graphical structures, including trapping sets, stopping sets, and absorbing sets that are frequently used
Eric Psota, Lance C. Pérez
doaj +1 more source
On‐Chip Photonic Neural Network Architectures
This review presents a comprehensive overview of on‐chip photonic neural network architectures, covering key photonic building blocks, representative network types, and emerging applications. Recent advances, implementation challenges, and future directions are examined, highlighting the potential of integrated photonics to enable ultrafast, energy ...
Seokjin Hong +7 more
wiley +1 more source
Optimum non-iterative turbo-decoding [PDF]
By observing the structure of the decoder's trellis a new, non-iterative turbo-decoder based on a super-trellis structure is proposed, which exhibits the same decoding complexity as a conventional convolutional decoder possessing an identical number of trellis states.
Marco Breiling, Lajos Hanzo
openaire +1 more source
Information Transmission Strategies for Self‐Organized Robotic Aggregation
In this review, we discuss how information transmission influences the neighbor‐based self‐organized aggregation of swarm robots. We focus specifically on local interactions regarding information transfer and categorize previous studies based on the functions of the information exchanged.
Shu Leng +5 more
wiley +1 more source
Iterative Syndrome-Based Deep Neural Network Decoding
While the application of deep neural networks (DNNs) for channel decoding is a well-researched topic, most studies focus on hard output decoding, potentially restricting the practical application of such decoders in real communication systems.
Dmitry Artemasov +3 more
doaj +1 more source
Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley +1 more source
Turbo codes and turbo algorithms
In the first part of this paper, several basic ideas that prompted the coming of turbo codes are commented on. We then present some personal points of view on the main advances obtained in past years on turbo coding and decoding such as the circular ...
Claude Berrou, Charlotte Langlais, Yi Yu
doaj

