Juan Aguero

Dr. Juan Aguero

Universidad Técnica Federico Santa María
orcid

Research Focus & Metrics

Academic Career Length

25Years (2002-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
1 September 2011 in Automatica
Verified
Journal Article
Closed access
BGBoris I. Godoy
Boris I. Godoy
GGGraham C. Goodwin
Graham C. Goodwin
JAJuan Aguero
Juan Aguero
DMDamián Marelli
Damián Marelli
TWTorbjörn Wigren
Torbjörn Wigren

1 December 2014 in Automatica
Verified
Journal Article
Closed access
SKSteffi Knorn
Steffi Knorn
ADAlejandro Donaire
Alejandro Donaire
JAJuan Aguero
Juan Aguero
RMRichard H. Middleton
Richard H. Middleton

10 September 2013 in IEEE Control Systems
Verified
Journal Article
Closed access
GGGraham C. Goodwin
Graham C. Goodwin
JAJuan Aguero
Juan Aguero
MGMauricio E. Cea Garridos
Mauricio E. Cea Garridos
MSMario E. Salgado
Mario E. Salgado
JYJuan I. Yuz
Juan I. Yuz
Modern signal processing and control algorithms are invariably implemented digitally, yet most real-world systems evolve in continuous time. Hence, the interaction between sampling and the behavior of continuous-time systems is an important ingredient in all real-world signals and systems problems.

1 February 2008 in Automatica
Verified
Journal Article
Closed access
JAJuan Aguero
Juan Aguero
GGGraham C. Goodwin
Graham C. Goodwin

1 February 2010 in Automatica
Verified
Journal Article
Closed access
JAJuan Aguero
Juan Aguero
JYJuan I. Yuz
Juan I. Yuz
GGGraham C. Goodwin
Graham C. Goodwin
RDRamon A. Delgado
Ramon A. Delgado

1 January 2007
Verified
Conference Paper
Closed access
JAJuan Aguero
Juan Aguero
GGGraham C. Goodwin
Graham C. Goodwin
JYJuan I. Yuz
Juan I. Yuz
In this paper we consider the problem of identification of linear systems using quantized data. We argue that, where possible, it is desirable to not utilize "naively" quantized data but instead it is preferable to choose the quantization mechanism carefully. In particular, we show that using a generalized noise shaping coder improves the accuracy of the estimates. We examine the accuracy of estimates for both naive and coded quantizers.