Results 111 to 120 of about 737,076 (296)
On Optimizing the PAPR of OFDM Signals With Coding, Companding, and MIMO
IEEE Access, 2019 One main disadvantage of the multiple-input-multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) system is that the signals transmitted on each antenna may experience high peak-to-average-power ratio (PAPR). We will present a new hybrid
Francisco Sandoval +2 more
doaj +1 more source
Advanced Science, EarlyView.Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li +6 more
wiley +1 more source
Deep Ensemble of Weighted Viterbi Decoders for Tail-Biting Convolutional Codes. [PDF]
Entropy (Basel), 2021 Raviv T, Schwartz A, Be'ery Y.
europepmc +1 more source
Ternary Trellis Coded Modulation
IEEE Access, 2019 Ternary trellis coded modulation (TTCM) is introduced. This combines triangular signal constellations with ternary convolutional codes. The performance of TTCM is presented and compared with binary trellis coded modulation (BTCM) which employs square ...
Mahmoud Abdelaziz, T. Aaron Gulliver
doaj +1 more source
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Advanced Science, EarlyView.Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
, 2019 We study multidimensional analogues of quasi-twisted codes from different points of view. Their concatenated structure allows us to characterize self-dual and complementary-dual classes of such codes as well as to show that multidimensional quasi-twisted
Özkaya, Buket, Ling, San
core +1 more source
Advanced Science, EarlyView.By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin +12 more
wiley +1 more source
Asymptotically good convolutional codes [PDF]
Linear and Multilinear Algebra, 2018 In this paper, we construct new sequences of asymptotically good convolutional codes. These sequences are obtained from sequences of transitive, self-orthogonal and self-dual block codes that attain the Tsfasman-Vladut-Zink bound. Furthermore, by applying the techniques of expanding, extending, puncturing, direct sum, the |u|u+v| construction and the ...
openaire +3 more sources
Broadening Hard‐Magnet Discovery Beyond Symmetry Constraints via Unified Effective Anisotropy
Advanced Science, EarlyView.A unified effective‐anisotropy descriptor (Keff) extends hard‐magnet screening across all seven crystal systems, beyond the uniaxial restriction of conventional searches. Machine‐learning screening of 9320 known ferromagnets and diffusion‐model generation together yield 38 rare‐earth‐free or ‐lean candidates with DFT‐validated magnetic hardness (κ > 1),
Hojae Kim +5 more
wiley +1 more source
Ferroelectric Devices for In‐Memory and In‐Sensor Computing
Advanced Science, EarlyView.Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang +5 more
wiley +1 more source