Results 11 to 20 of about 23,384 (296)

Computing high-degree polynomial gradients in memory [PDF]

Nature Communications
Specialized function gradient computing hardware could greatly improve the performance of state-of-the-art optimization algorithms. Prior work on such hardware, performed in the context of Ising Machines and related concepts, is limited to quadratic ...
Tinish Bhattacharya, George H. Hutchinson, Giacomo Pedretti, Xia Sheng, Jim Ignowski, Thomas Van Vaerenbergh, Ray Beausoleil, John Paul Strachan, Dmitri B. Strukov   +8 more
doaj   +7 more sources

FourierPIM: High-throughput in-memory Fast Fourier Transform and polynomial multiplication

Memories - Materials, Devices, Circuits and Systems, 2023
The Discrete Fourier Transform (DFT) is essential for various applications ranging from signal processing to convolution and polynomial multiplication. The groundbreaking Fast Fourier Transform (FFT) algorithm reduces DFT time complexity from the naive O(
Orian Leitersdorf, Yahav Boneh, Gonen Gazit, Ronny Ronen, Shahar Kvatinsky   +4 more
doaj   +3 more sources

Nonlinear compensation with DBP aided by a memory polynomial [PDF]

Optics Express, 2016
Using digital backpropagation (DBP) based on the split step Fourier method (SSFM) aided by a memory polynomial (MP) model, we demonstrate an improved DBP approach for fiber nonlinearity compensation. The proposed technique (DBP-SSFM&MP) is numerically validated and its performance and complexity are compared against the benchmark DBP-SSFM, considering ...
Gonçalves, João, Martins, Celestino S., PEREIRA GUIOMAR, FERNANDO PEDRO, Cunha, Telmo R., Pedro, José C., Pinto, Armando N., Lavrador, Pedro M.   +6 more
openaire   +4 more sources

Design of Reliable, Resilient, and Robust Architecture and Control for Next-Generation Optical-Wireless Networks. [PDF]

Sensors (Basel)
The convergence of optical transport and wireless access in next- and future-generation networks imposes strict QoS demands, particularly end-to-end reliability, which conventional redundancy approaches cannot meet.
Nleya B, Pule B.
europepmc   +2 more sources

Orthogonal Polynomial-Based Nonlinearity Modeling and Mitigation for LED Communications

IEEE Photonics Journal, 2016
The light-emitting diode (LED) is the major source of nonlinearity in LED communications, and the nonlinearity needs to be effectively modeled and thereby mitigated through predistortion or postdistortion to avoid degradation of communication performance.
Weikang Zhao, Qinghua Guo, Jun Tong, Jiangtao Xi, Yanguang Yu, Pingjuan Niu, Xiaohong Sun   +6 more
doaj   +2 more sources

Robust Fractional Order Memory Polynomial Based Pre-Distorter

IEICE Transactions on Communications, 2011
In this paper, a robust fractional order memory polynomial pre-distorter with two novel schemes to conduct digital base-band power amplifier pre-distortion is proposed. For the first scheme, fractional order terms are included in the conventional memory polynomial containing the odd and even order polynomial terms, which is called Scheme One.
Ai, Bo, Zhong, Zhangdui, Li, Bo, Ma, Linhua   +3 more
openaire   +3 more sources

Smoking dynamics with media awareness to control the prevalence of bad effect through fractional operator study. [PDF]

MethodsX
Smoking remains a persistent global health concern with complex behavioral dynamics influenced by memory and past experiences. This study formulates and analyses a fractional-order mathematical model of smoking behavior using the Caputo derivative to ...
Farman M, Alfiniyah C, Jamil K, Sambas A, Millah N, Ahmadin.   +5 more
europepmc   +2 more sources

Minimal-Memory, Noncatastrophic, Polynomial-Depth Quantum Convolutional Encoders [PDF]

IEEE Transactions on Information Theory, 2013
Quantum convolutional coding is a technique for encoding a stream of quantum information before transmitting it over a noisy quantum channel. Two important goals in the design of quantum convolutional encoders are to minimize the memory required by them and to avoid the catastrophic propagation of errors.
Monireh Houshmand, Saied Hosseini-Khayat, Mark M. Wilde   +2 more
openaire   +4 more sources

Limited memory predictors based on polynomial approximation of periodic exponentials

Journal of Forecasting, 2022
AbstractThe paper presents transfer functions for limited memory time‐invariant linear integral predictors for continuous time processes such that the corresponding predicting kernels have bounded support. It is shown that processes with exponentially decaying Fourier transforms are predictable with these predictors in some weak sense, meaning that ...
Dokuchaev, Nikolai
openaire   +3 more sources

Cross-Memory Polynomial Modeling for RF Circuits [PDF]

, 2012
A new behavioral model is proposed which can provide similar accuracy to the memory polynomial model (MPM) but is shown to have a more efficient architecture for digital hardware implementation. These features have been achieved by the proposed formulation, in which the nonlinear weights of the memory terms are a function of only the present input ...
Farsi, Saeed, Schreurs, Dominique, Nauwelaers, Bart, Dooley, John, Finnerty, Keith, Farrell, Ronan   +5 more
openaire   +2 more sources