Hardware implementation of real-time Extreme Learning Machine in FPGA: Analysis of precision, resource occupation and performance

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FPGA Implementation of Modified Gram-Schmidt QR-Decomposition

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An IP Core and GUI for Implementing Multilayer Perceptron with a Fuzzy Activation Function on Configurable Logic Devices

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Soil moisture forecasting by a hybrid machine learning technique: ELM integrated with ensemble empirical mode decomposition

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Embedded Intelligence on FPGA: Survey, Applications and Challenges

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A Neural Network-Based On-device Learning Anomaly Detector for Edge Devices

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Swarm-based optimization as stochastic training strategy for estimation of reference evapotranspiration using extreme learning machine

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A Novel Systolic Parallel Hardware Architecture for the FPGA Acceleration of Feedforward Neural Networks

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Microgrid protection under wind speed intermittency using extreme learning machine

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System-on-a-Chip (SoC)-Based Hardware Acceleration for an Online Sequential Extreme Learning Machine (OS-ELM)

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Neuromorphic extreme learning machines with bimodal memristive synapses

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A Maximally Split and Relaxed ADMM for Regularized Extreme Learning Machines

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Automated Detection of Epileptic Biomarkers in Resting-State Interictal MEG Data

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Deep Layer Kernel Sparse Representation Network for the Detection of Heart Valve Ailments from the Time‐Frequency Representation of PCG Recordings

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A Digital Implementation of Extreme Learning Machines for Resource-Constrained Devices

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Moving Learning Machine towards Fast Real-Time Applications: A High-Speed FPGA-Based Implementation of the OS-ELM Training Algorithm

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Efficient hardware implementation of radial basis function neural network with customized-precision floating-point operations

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Genetic Algorithm-Optimized Extreme Learning Machine Model for Estimating Daily Reference Evapotranspiration in Southwest China

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OS-ELM-FPGA: An FPGA-Based Online Sequential Unsupervised Anomaly Detector

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AnScalable Matrix Computing Unit Architecture for FPGA, and SCUMO User Design Interface

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System-on-a-chip (SoC)-based hardware acceleration for extreme learning machine

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Extreme learning machine as a generalizable classification engine

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FPGA‐based favourite skin colour restoration using improved histogram equalization with variable enhancement degree and ensemble extreme learning machine

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An experimental evaluation of extreme learning machines on several hardware devices

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A versatile hardware/software platform for personalized driver assistance based on online sequential extreme learning machines

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A Novel Relaxed ADMM with Highly Parallel Implementation for Extreme Learning Machine

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Accelerating Extreme Learning Machine on FPGA by Hardware Implementation of Given Rotation-QRD

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A generic FPGA-based hardware architecture for recursive least mean p-power extreme learning machine

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Design of an Optimized CMOS ELM Accelerator

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A Task-Parallel and Reconfigurable FPGA-Based Hardware Implementation of Extreme Learning Machine

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Benchmarking Hardware Accelerating Techniques for Extreme Learning Machine

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Scalable IP Core for Feed Forward Random Networks

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Digital Implementation of OS-ELM for Data Classification in Real-Time

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FPGA Implementation of WRVFLN for Classification

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Aceleração de hardware em sistemas embarcados para aprendizado de máquina utilizando KNN em FPGA

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Implemetasi Komputasi Akar Kuadrat Resolusi Tinggi pada Field Programmable Gate Array (FPGA)

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FPGA Simulation for Computing Pseudoinverse Matrices

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Hardware Implementation of MRO-ELM for Online Sequential Learning on FPGA

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FPGA based Matrix Multiplication Accelerator

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Experimental FPGA for classification tasks with the extreme learning machine model

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Novel Simplified Analog Neuron in CMOS Technology with Digital Weights

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A Task-Parallel and Reconfigurable FPGA-Based Hardware Implementation of Extreme Learning Machine

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A generic FPGA-based hardware architecture for recursive least mean p-power extreme learning machine

Huang, H. M., Yang, J., Rong, H.-J., & Du, S. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.05.069 · Cited by 3 · see citing works

FPGA implementation of extreme learning machine system for classification

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FPGA Implementation of Random Feature Mapping in ELM Algorithm for Binary Classification

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Accelerating Extreme Learning Machine on FPGA by Hardware Implementation of Given Rotation-QRD

Tan, C. Y., Ismail, N. B., Ooi, C. Y., & Hon, J. Y. (2019) · International Journal of Integrated Engineering · doi:10.30880/ijie.2019.11.07.005 · Cited by 3 · see citing works