scholarly journals Regularization Factor Selection Method for l1-Regularized RLS and Its Modification against Uncertainty in the Regularization Factor

2019 ◽  
Vol 9 (1) ◽  
pp. 202 ◽  
Author(s):  
Junseok Lim ◽  
Seokjin Lee
Keyword(s):  
Impulse Response ◽  
Conventional Method ◽  
Calculation Method ◽  
A Priori ◽  
Selection Method ◽  
Impulse Responses ◽  
New Model ◽  
Channel Response ◽  
Channel Information ◽  
Sparse Impulse Response

This paper presents a new l1-RLS method to estimate a sparse impulse response estimation. A new regularization factor calculation method is proposed for l1-RLS that requires no information of the true channel response in advance. In addition, we also derive a new model to compensate for uncertainty in the regularization factor. The results of the estimation for many different kinds of sparse impulse responses show that the proposed method without a priori channel information is comparable to the conventional method with a priori channel information.

scholarly journals Balancing and Simulation of a Double Crank-Rocker Engine Model for Optimum Reduction of Shaking Forces and Shaking Moments

2021 ◽  
Vol 8 (2) ◽  
pp. 237-245
Author(s):  
Anwr M. Albaghdadi ◽  
Masri B. Baharom ◽  
Shaharin A. Sualiman
Keyword(s):  
Dynamic Analysis ◽  
Objective Function ◽  
Conventional Method ◽  
Optimization Process ◽  
New Model ◽  
Engine Model ◽  
Design Variables ◽  
Driving Torque ◽  
Related Design ◽  
Shaking Moment

In this paper, a new configuration of Crank-Rocker (CR) model has been proposed by duplicating its mechanism. The method has been implemented to overcome vibration problem on a single-piston Crank-Rocker engine caused by system unbalance. The new method suggests combining conventional method of adding counterweights to reduce shaking forces and eliminating the inertial moments on system by implementing the new layout. A dynamic study of the new model is presented, then the objective function is derived and implemented to perform the optimization process. Related design variables and system constraints are introduced to determine attached counterweights optimized characteristics. For results validation, the simulation, dynamic analysis, and optimization process were conducted using ADAMS VIEW® software. The output results were presented and discussed to verify the validity of the suggested method. It was noticed that the method was very effective and has managed to reduce the total shaking forces by about 91%, shaking moment by about 66%; and the driving torque by 27%.

Vibration Based Modal Parameters Identification and Wear Fault Diagnosis Using Laplace Wavelet

2005 ◽  
Vol 293-294 ◽  
pp. 183-192 ◽  
Author(s):  
Yanyang Zi ◽  
Xue Feng Chen ◽  
Zheng Jia He ◽  
Peng Chen
Keyword(s):  
Fault Diagnosis ◽  
Impulse Response ◽  
Combustion Engine ◽  
Intake Valve ◽  
Impulse Responses ◽  
Transient Responses ◽  
Vibration Signals ◽  
Modal Parameters Identification ◽  
Non Stationary Signal ◽  
Correlation Filtering

Wavelet transform is a powerful technique well suited to non-stationary signal processing. The properties of wavelet are determined by its basis function. In the fields of modal analysis, mechanical condition monitoring and fault diagnosis, impulse responses or transient responses are very common signals to be analyzed. The Laplace wavelet is a single-sided damped exponential wavelet and is a desirable wavelet basis to analyze signals of impulse response. A correlation filtering approach is introduced using the Laplace wavelet to identify the impulse response from vibration signals. Successful results are obtained in identifying the natural frequency of a hydro-generator shaft, and diagnosing the wear fault of intake valve of an internal combustion engine.

scholarly journals Impulse response of a generalized fractional second order filter

2012 ◽  
Vol 15 (1) ◽  
Author(s):  
Zhuang Jiao ◽  
YangQuan Chen
Keyword(s):  
Impulse Response ◽  
Stability Property ◽  
Asymptotic Properties ◽  
Second Order ◽  
Impulse Responses ◽  
Critical Stability ◽  
Numerical Examples ◽  
Order Filter

AbstractThe impulse response of a generalized fractional second order filter of the form (s 2α + as α + b)−γ is derived, where 0 < α ≤ 1, 0 < γ < 2. The asymptotic properties of the impulse responses are obtained for two cases, and within these two cases, the properties are shown when changing the value of γ. It is shown that only when (s 2α + as α + b)−1 has the critical stability property, the generalized fractional second order filter (s 2α + as α + b)−γ has different properties as we change the value of γ. Finally, numerical examples to illustrate the impulse response are provided to verify the obtained results.

THE PRICE PUZZLE AND VAR IDENTIFICATION

2014 ◽  
Vol 19 (8) ◽  
pp. 1880-1887 ◽  
Author(s):  
Arturo Estrella
Keyword(s):  
Monetary Policy ◽  
Impulse Response ◽  
Response Function ◽  
Impulse Response Function ◽  
Reduced Form ◽  
Impulse Responses ◽  
Minimal Set ◽  
Price Puzzle ◽  
Single Term ◽  
Structural Vars

In structural VARs, unexpected monetary tightening often leads to the price puzzle, a counterintuitive increase in inflation in the impulse response function. The identification of impulse responses requires at least a minimal set of structural assumptions, and models exhibiting the price puzzle typically use standard assumptions focusing mainly on relationships among contemporaneous disturbances. This note uses a well-established stylized fact, the long lags of monetary policy, to motivate a simple additional identifying assumption. The assumption eliminates a single term in one equation of the reduced form, and with it the price puzzle.

Analyzing operators of 3-D imaging software with impulse responses

Geophysics ◽  
1999 ◽  
Vol 64 (4) ◽  
pp. 1079-1092 ◽  
Author(s):  
William A. Schneider
Keyword(s):  
Impulse Response ◽  
Imaging Techniques ◽  
Velocity Model ◽  
Impulse Responses ◽  
Step Size ◽  
Data Set ◽  
Time Migration ◽  
Offset Time ◽  
Zero Offset ◽  
Algorithm Implementation

No processing step changes seismic data more than 3-D imaging. Imaging techniques such as 3-D migration and dip moveout (DMO) generally change the position, amplitude, and phase of reflections as they are converted into reflector images. Migration and DMO may be formulated in many different ways, and various algorithms are available for implementing each formulation. These algorithms all make physical approximations, causing imaging software to vary with algorithm choice. Imaging software also varies because of additional implementation approximations, such as those that trade accuracy for efficiency. Imaging fidelity, then, generally depends upon algorithm, implementation, specific software parameters (such as aperture, antialias filter settings, and downward‐continuation step size), specific acquisition parameters (such as nominal x- and y-direction trace spacings and wavelet frequency range), and, of course, the velocity model. Successfully imaging the target usually requires using appropriate imaging software, parameters, and velocities. Impulse responses provide an easy way to quantitatively understand the operators of imaging software and then predict how specific imaging software will perform with the chosen parameters. (An impulse response is the image computed from a data set containing only one nonzero trace and one arrival on that trace.) I have developed equations for true‐amplitude impulse responses of 3-D prestack time migration, 3-D zero‐offset time migration, 3-D exploding‐reflector time migration, and DMO. I use these theoretical impulse responses to analyze the operators of actual imaging software for a given choice of software parameters, acquisition parameters, and velocity model. The procedure is simple: compute impulse responses of some software; estimate position, amplitude, and phase of the impulse‐response events; and plot these against the theoretical values. The method is easy to use and has proven beneficial for analyzing general imaging software and for parameter evaluation with specific imaging software.

Digital simulation of photoacoustic impulse responses

1986 ◽  
Vol 64 (9) ◽  
pp. 1049-1052 ◽  
Author(s):  
Richard M. Miller
Keyword(s):  
Finite Difference ◽  
Impulse Response ◽  
Depth Distribution ◽  
Digital Simulation ◽  
Heat Diffusion ◽  
Finite Difference Approximation ◽  
Diffusion Equations ◽  
Difference Approximation ◽  
Impulse Responses ◽  
Solid Samples

Impulse-response photoacoustic spectroscopy provides information on the depth distribution of chromophores in solid samples. To gain an understanding of the way in which sample properties affect the impulse response, a digital model has been generated. This model is based on discretization of time and space coupled with a finite-difference approximation of the governing heat-diffusion equations. The simulations are compared with experimental results.

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