Low-order Nonlinear Finite-Impulse Response Soft Sensors for Ionic Electroactive Actuators Based on Deep Learning

2019 ◽  
Vol 68 (5) ◽  
pp. 1637-1646 ◽  
Author(s):  
Bruno Ando ◽  
Salvatore Graziani ◽  
Maria Gabriella Xibilia
Keyword(s):  
Deep Learning ◽  
Impulse Response ◽  
Finite Impulse Response ◽  
Soft Sensors ◽  
Low Order

scholarly journals NANO-studio, the design environment of filter banks implemented in standard CMOS technology

2021 ◽  
Author(s):  
Andrzej Handkiewicz ◽  
Mariusz Naumowicz
Keyword(s):  
Impulse Response ◽  
Filter Banks ◽  
Finite Impulse Response ◽  
Infinite Impulse Response ◽  
Cmos Process ◽  
Digital Cmos ◽  
Additional Advantage ◽  
Analysis And Synthesis ◽  
Optimization Parameters ◽  
Synthesis Filter

AbstractThe paper presents a method of optimizing frequency characteristics of filter banks in terms of their implementation in digital CMOS technologies in nanoscale. Usability of such filters is demonstrated by frequency-interleaved (FI) analog-to-digital converters (ADC). An analysis filter present in these converters was designed in switched-current technique. However, due to huge technological pitch of standard digital CMOS process in nanoscale, its characteristics substantially deviate from the required ones. NANO-studio environment presented in the paper allows adjustment, with transistor channel sizes as optimization parameters. The same environment is used at designing a digital synthesis filter, whereas optimization parameters are input and output conductances, gyration transconductances and capacitances of a prototype circuit. Transition between analog s and digital z domains is done by means of bilinear transformation. Assuming a lossless gyrator-capacitor (gC) multiport network as a prototype circuit, both for analysis and synthesis filter banks in FI ADC, is an implementation of the strategy to design filters with low sensitivity to parameter changes. An additional advantage is designing the synthesis filter as stable infinite impulse response (IIR) instead of commonly used finite impulse response (FIR) filters. It provides several dozen-fold saving in the number of applied multipliers.. The analysis and synthesis filters in FI ADC are implemented as filter pairs. An additional example of three-filter bank demonstrates versatility of NANO-studio software.

FINITE IMPULSE RESPONSE DOUBLE DENSITY FILTER BANKS AND FRAMELETS

2013 ◽  
Vol 11 (01) ◽  
pp. 1350010
Author(s):  
ASHOKA JAYAWARDENA ◽  
PAUL KWAN
Keyword(s):  
Wavelet Transform ◽  
Impulse Response ◽  
Filter Bank ◽  
Filter Banks ◽  
Finite Impulse Response ◽  
Wavelet Filters ◽  
Density Filter ◽  
Shift Invariance ◽  
Factorization Methods ◽  
Invariant Properties

In this paper, we focus on the design of oversampled filter banks and the resulting framelets. The framelets obtained exhibit improved shift invariant properties over decimated wavelet transform. Shift invariance has applications in many areas, particularly denoising, coding and compression. Our contribution here is on filter bank completion. In addition, we propose novel factorization methods to design wavelet filters from given scaling filters.

A Finite-Impulse-Response-Based Approach to Control Acoustic-Caused Probe-Vibration in Atomic Force Microscope Imaging

2017 ◽  
Author(s):  
Sicheng Yi ◽  
Qingze Zou
Keyword(s):  
Atomic Force Microscope ◽  
Impulse Response ◽  
Controller Design ◽  
Finite Impulse Response ◽  
Feedforward Control ◽  
Acoustic Noise ◽  
Noise Cancellation ◽  
Control Approach ◽  
Atomic Force ◽  
Afm Imaging

In this paper, we propose a finite-impulse-response (FIR)-based feedforward control approach to mitigate the acoustic-caused probe vibration during atomic force microscope (AFM) imaging. Compensation for the extraneous probe vibration is needed to avoid the adverse effects of environmental disturbances such as acoustic noise on AFM imaging, nanomechanical characterization, and nanomanipulation. Particularly, residual noise still exists even though conventional passive noise cancellation apparatus has been employed. The proposed technique exploits a data-driven approach to capture both the noise propagation dynamics and the noise cancellation dynamics in the controller design, and is illustrated through the experimental implementation in AFM imaging application.

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