P
Peter Grant
Researcher at University of Edinburgh
Publications - 308
Citations - 13399
Peter Grant is an academic researcher from University of Edinburgh. The author has contributed to research in topics: Adaptive filter & Spread spectrum. The author has an hindex of 44, co-authored 307 publications receiving 12837 citations. Previous affiliations of Peter Grant include Massachusetts Institute of Technology & Stanford University.
Papers
More filters
Journal ArticleDOI
Orthogonal least squares learning algorithm for radial basis function networks
TL;DR: The authors propose an alternative learning procedure based on the orthogonal least-squares method, which provides a simple and efficient means for fitting radial basis function networks.
Journal ArticleDOI
Non-linear system identification using neural networks
TL;DR: This paper investigates the identification of discrete-time nonlinear systems using neural networks with a single hidden layer using new parameter estimation algorithms derived for the neural network model based on a prediction error formulation.
Journal ArticleDOI
A clustering technique for digital communications channel equalization using radial basis function networks
TL;DR: It is shown that the radial basis function network has an identical structure to the optimal Bayesian symbol-decision equalizer solution and, therefore, can be employed to implement the Bayesian equalizer.
Journal ArticleDOI
Green radio: radio techniques to enable energy-efficient wireless networks
Congzheng Han,T Harrold,Simon Armour,Ioannis Krikidis,Stefan Videv,Peter Grant,Harald Haas,John Thompson,Ivan Ku,Cheng-Xiang Wang,Tuan Anh Le,M. Reza Nakhai,Jiayi Zhang,Lajos Hanzo +13 more
TL;DR: The technical background to the VCE Green Radio project is discussed, models of current energy consumption in base station devices are discussed and some of the most promising research directions in reducing the energy consumption of future base stations are described.
Journal ArticleDOI
Spatial modulation for multiple-antenna wireless systems: a survey
TL;DR: Spatial Modulation is a novel and recently proposed multiple-antenna transmission technique that can offer, with a very low system complexity, improved data rates compared to Single-Input- Single-Output (SISO) systems, and robust error performance even in correlated channel environments.