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Article in MDPI journal

May 2021, UPM published the work “A Secure and Scalable Smart Home Gateway to Bridge Technology Fragmentation” Abstract Internet of Things (IoT) technologies are already playing an important role in our daily activities as we use them and rely on them to increase our abilities, connectivity, productivity and quality of life. However, there are still […]

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Article in SpringerLink Behavior Research Methods

April, 2021 DPZ published the work “The cone method: Inferring decision times from single-trial 3D movement trajectories in choice behavior“ Abstract Ongoing goal-directed movements can be rapidly adjusted following new environmental information, e.g., when chasing pray or foraging. This makes movement trajectories in go-before-you-know decision-making a suitable behavioral readout of the ongoing decision process. Yet, […]

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Article in Nature communication biology journal

March, 2021, UGOE published the work “Memory consolidation and improvement by synaptic tagging and capture in recurrent neural networks” Abstract The synaptic-tagging-and-capture (STC) hypothesis formulates that at each synapse the concurrence of a tag with protein synthesis yields the maintenance of changes induced by synaptic plasticity. This hypothesis provides a biological principle underlying the synaptic […]

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Article in Frontiers NeuroRobotics Journal

November, 2020 UGOE published the work “Robust Trajectory Generation for Robotic Control on the Neuromorphic Research Chip Loihi“ Abstract Neuromorphic hardware has several promising advantages compared to von Neumann architectures and is highly interesting for robot control. However, despite the high speed and energy efficiency of neuromorphic computing, algorithms utilizing this hardware in control scenarios […]

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Article in Frontiers Neural Circuits Journal

October, 2020 UGOE published the work “The Interplay of Synaptic Plasticity and Scaling Enables Self-Organized Formation and Allocation of Multiple Memory Representations“ Abstract It is commonly assumed that memories about experienced stimuli are represented by groups of highly interconnected neurons called cell assemblies. This requires allocating and storing information in the neural circuitry, which happens […]

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Article Published in 2020 IEEE International Conference on Real-time Computing and Robotics (RCAR)

September, 2020 SDU published the work “Autobot for Effective Design Space Exploration and Agile Generation of RBFNN Hardware Accelerator in Embedded Real-time Computing“ Abstract This paper presents a method of employing Auto-bot to replace humans in the task of efficient hardware design for radial basis function neural network (RBFNN) in real-time computing applications. Autobot applies […]

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Article in 2020 IEEE International Conference on Consumer Electronics – Taiwan (ICCE-Taiwan)

September, 2020 SDU published the work “End-to-End Rapid FPGA Prototyping for Embedded Proactive BMI Control“ Abstract This paper presents an end-to-end rapid prototyping methodology that performs automated and efficient mapping of desired neural networks onto FPGA. The design automation agent is considered as Autobot. An early prototype with the hardware decoder generated on the FPGA […]

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Article in Frontiers Neural Circuits Journal

August, 2020 SDU published the work “General Distributed Neural Control and Sensory Adaptation for Self-Organized Locomotion and Fast Adaptation to Damage of Walking Robots“ Abstract Walking animals such as invertebrates can effectively perform self-organized and robust locomotion. They can also quickly adapt their gait to deal with injury or damage. Such a complex achievement is […]

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