Digital signal processing
Robust and optimal control
Digital Controller Implementation and Fragility: A Modern Perspective
Digital Controller Implementation and Fragility: A Modern Perspective
Parametrizations in Control, Estimation, and Filtering Problems: Accuracy Aspects
Parametrizations in Control, Estimation, and Filtering Problems: Accuracy Aspects
Digital Control and Estimation: A Unified Approach
Digital Control and Estimation: A Unified Approach
Fixed-point configurable hardware components
EURASIP Journal on Embedded Systems
Quantization Noise: Roundoff Error in Digital Computation, Signal Processing, Control, and Communications
Low-parametric-sensitivity realizations with relaxed L2-dynamic-range-scaling constraints
IEEE Transactions on Circuits and Systems II: Express Briefs
Improved Interval-Based Characterization of Fixed-Point LTI Systems With Feedback Loops
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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Input-output or poles sensitivity is widely used to evaluate the resilience of a filter realization to coefficients quantization in an FWL implementation process. However, these measures do not exactly consider the various implementation schemes and are not accurate in general case. This paper generalizes the classical transfer function sensitivity and pole sensitivity measure, by taking into consideration the exact fixed-point representation of the coefficients. Working in the general framework of the specialized implicit descriptor representation, it shows how a statistical quantization error model may be used in order to define stochastic sensitivity measures that are definitely pertinent and normalized. The general framework of MIMO filters and controllers is considered. All the results are illustrated through an example.