12 citations · 37 across the 18 of their papers we have counts for
6 papers · 1 filter
Adaptive function approximation based on the Discrete Cosine Transform (DCT)
Ana I. Pérez-Neira, Marc Martinez-Gost, Miguel Ángel Lagunas
This paper studies the cosine as basis function for the approximation of univariate and continuous functions without memory. This work studies a supervised learning to obtain the a…
LoRa Modulation for Split Learning
Marc Martinez-Gost, Ana Pérez-Neira, Miguel Ángel Lagunas
In this paper we introduce a task-oriented communication design for split learning (SL) over a communication channel. Our approach involves the Expressive Neural Network (ENN), a n…
ENN: A Neural Network with DCT Adaptive Activation Functions
Marc Martinez-Gost, Ana Pérez-Neira, Miguel Ángel Lagunas
The expressiveness of neural networks highly depends on the nature of the activation function, although these are usually assumed predefined and fixed during the training stage. Un…
LoRa-based Over-the-Air Computing for Sat-IoT
Marc Martinez-Gost, Ana Pérez-Neira, Miguel Ángel Lagunas
Satellite Internet of Things (Sat-IoT) is a novel framework in which satellites integrate sensing, communication and computing capabilities to carry out task-oriented communication…
DCT-based Air Interface Design for Function Computation
Marc Martinez-Gost, Ana Pérez-Neira, Miguel Ángel Lagunas
With the integration of communication and computing, it is expected that part of the computing is transferred to the transmitter side. In this paper we address the general problem…
Frequency Modulation Aggregation for Federated Learning
Marc Martinez-Gost, Ana Pérez-Neira, Miguel Ángel Lagunas
Federated edge learning (FEEL) is a framework for training models in a distributed fashion using edge devices and a server that coordinates the learning process. In FEEL, edge devi…