… the complexity of the decoder via deep learning [19]–[21]. Learning a … Deep learning based
modulation design has been studied in various … We consider two types of power constraints: …

… In this paper, we construct KO codes, a computationaly efficient family of deep-learning
driven (encoder, decoder) pairs that … Here we consider the hard power constraint, ie, x2 = n. …

… with the cascaded reformulation of the parity check (PC) constraints [2], we propose to …
increase the decoding performance. Essentially, we provide a deep learning-based method to …

… a new class of codes under low-latency constraints, which we call … On deep learning-based
channel decoding. In2017 51st … Scaling deep learning-based decoding of polar codes via …

… order to extract features, cis processed by decoding blocks with parameters θ1, θ2, ··· θm. In
other words, we decode c for a known coding … Constraint length is 5 and information length …

… In order to constrain the high complexity of SCL decoding, at each bit estimation, a set of
only L candidates are allowed to survive, based on a path metric that is calculated as (…

… codes in this paper, DL-based code design and decoding … design problem belongs to
the class of nonlinear constraint … a learning-based approach to adapt the required order …

… strands are decoded by DNA sequencing (… and decoding techniques are employed, comprising
computational and mathematical models. In BT, DNA synthesis, storage, and sequencing …

… in this tutorial, enforces a soft power constraint and allows real-valued … deep learning
based communication system for channels with output feedback: both the encoder and decoder …

… The above reviewed ∞-constrained image coding approach … of ∞-constrained encoding and
deep soft decoding ( ∞-ED2), … the-art deep learning based compression methods proposed …