scholarly journals An Alternative Approach to the Balanced Model Truncation Algorithm for Acoustic Minimum-Phase Inverse Filters Order Reduction

2011 ◽  
Vol 2011 ◽  
pp. 1-6
Author(s):  
Maamar Ahfir ◽  
Izzet Kale ◽  
Daoud Berkani
Keyword(s):  
Order Reduction ◽  
Standard Technique ◽  
Singular Values ◽  
Room Acoustics ◽  
Order Selection ◽  
Minimum Phase ◽  
Hankel Singular Values ◽  
Alternative Approach ◽  
Balanced Model ◽  
Selection Of

We propose an alternative approach to the Balanced Model Truncation method (standard method). This approach reduces substantially the order of minimum-phase inverse filters for equalizing room acoustics. This method is based on a property of the filter z transform function, which modifies the corresponding FIR coefficients before the application of the standard technique to the modified FIR coefficients filter version. In the standard technique, the Hankel singular values plot is the chief guide for a user for the selection of a reduced filter order. Results for minimum-phase inverse filter corresponding to partial equalization of measured acoustic impulse response show the superiority of the proposed method over the standard technique, in terms of reduced filters order selection.

Implementasi Algoritma MAX-MIN Ant System pada Penjadwalan Mata Kuliah

2013 ◽  
Vol 5 (2) ◽  
pp. 48-53
Author(s):  
William Aprilius ◽  
Lorentzo Augustino ◽  
Ong Yeremia M. H.
Keyword(s):  
Ant Colony Optimization ◽  
Ant Colony ◽  
Ant System ◽  
University Course Timetabling ◽  
Alternative Approach ◽  
Ant System Algorithm ◽  
Index Terms ◽  
Course Timetabling Problem ◽  
University Course ◽  
Selection Of

University Course Timetabling Problem is a problem faced by every university, one of which is Universitas Multimedia Nusantara. Timetabling process is done by allocating time and space so that the whole associated class and course can be implemented. In this paper, the problem will be solved by using MAX-MIN Ant System Algorithm. This algorithm is an alternative approach to ant colony optimization. This algorithm uses two tables of pheromones as stigmergy, i.e. timeslot pheromone table and room pheromone table. In addition, the selection of timeslot and room is done by using the standard deviation of the value of pheromones. Testing is carried out by using 105 events, 45 timeslots, and 3 types of categories based on the number of rooms provided, i.e. large, medium, and small. In each category, testing is performed 5 times and for each testing, the data recorded is the unplace and Soft Constraint Penalty. In general, the greater the number of rooms, the smaller the unplace. Index Terms—ant colony optimization, max-min ant system, timetabling

Analysis of multiplicity of Hankel singular values of control systems

2015 ◽  
Vol 76 (2) ◽  
pp. 205-218 ◽  
Author(s):  
L. A. Mironovskii ◽  
T. N. Solov’eva
Keyword(s):  
Control Systems ◽  
Singular Values ◽  
Hankel Singular Values

Selection of Component Modes for Craig-Bampton Substructure Representations

1996 ◽  
Vol 118 (2) ◽  
pp. 264-270 ◽  
Author(s):  
D. C. Kammer ◽  
M. J. Triller
Keyword(s):  
Efficient Method ◽  
Singular Values ◽  
General Purpose ◽  
Mode Shapes ◽  
Frequency Range ◽  
Reduced Representation ◽  
Absolute Measure ◽  
Fixed Interface ◽  
Interface Mode ◽  
Selection Of

Three measures of modal dynamic importance are studied for the purpose of ranking Craig-Bampton substructure fixed interface mode shapes based upon their contribution to forces at the substructure interface, modal velocity, or modal displacement. These measures can be employed to identify mode shapes which are dynamically important and thus should be retained in a reduced analytical representation, or identified during a modal survey of the substructure. The first method considered. Effective Interface Mass, has been studied previously. However, new results are presented showing the relation between Effective Interface Mass and a commonly used control dynamics measure of modal importance called approximate balanced singular values. In contrast to the general case of approximate balanced singular values, Effective Interface Mass always gives an absolute measure of the dynamic importance of mode shapes. The EIM method is extended to consider modal velocity and modal displacement outputs. All three measures are applied to a simple substructure called the General Purpose Spacecraft. It is shown that each of these measures provides an efficient method for ranking the dynamic importance of Craig-Bampton fixed interface modes such that a reduced representation will accurately reproduce the substructure’s response in the frequency range of interest.

Estimation of the Hankel Singular Values of Fractional-Order Systems

2009 ◽  
Author(s):  
Jay L. Adams ◽  
Robert J. Veillette ◽  
Tom T. Hartley
Keyword(s):  
Fractional Order ◽  
Dimensional Space ◽  
Ritz Method ◽  
Singular Values ◽  
Finite Dimensional Space ◽  
Fractional Order Systems ◽  
Norm Estimates ◽  
Finite Dimensional ◽  
Hankel Singular Values ◽  
Hankel Norm

This paper applies the Rayleigh-Ritz method to approximating the Hankel singular values of fractional-order systems. The algorithm is presented, and estimates of the first ten Hankel singular values of G(s) = 1/(sq+1) for several values of q ∈ (0, 1] are given. The estimates are computed by restricting the operator domain to a finite-dimensional space. The Hankel-norm estimates are found to be within 15% of the actual values for all q ∈ (0, 1].

data a; * significance level; a=0.05; * variance of difference of two observations on the log scale; * sigmaW = within-subjects standard deviation; sigmaW=0.355; s=sqrt(2)*sigmaW; * total number of subjects (needs to be a multiple of 2); n=58; * error degrees of freedom for AB/BA cross-over with n subjects in total; n2=n-2; * ratio = mu_T/mu_R; ratio=1.00; run; data b; set a; * calculate power; t1=tinv(1-a,n-2); t2=-t1; nc1=(sqrt(n))*((log(ratio)-log(0.8))/s); nc2=(sqrt(n))*((log(ratio)-log(1.25))/s); df=(sqrt(n-2))*((nc1-nc2)/(2*t1)); prob1=probt(t1,df,nc1); prob2=probt(t2,df,nc2); answer=prob2-prob1; power=answer*100; run; proc print data=b; run; As an example of using this SAS code, suppose µ = 1, σ = 0.355, α = 0.05 and n = 58. The power (as a percentage) is calculated as 90.4. The required number of subjects to achieve a given power can easily be obtained by trial and error using a selection of values of n. An alternative approach is to use trial and error directly on the sample size n for a given power. For more on this see Phillips (1990) and Diletti et al. (1991), for example. 7.4 Individual bioequivalence As noted in Section 7.1, individual bioequivalence (IBE) is a criterion for deciding if a patient who is currently being treated with R can be

2003 ◽  
pp. 362-362
Keyword(s):  
Standard Deviation ◽  
Sample Size ◽  
Degrees Of Freedom ◽  
Trial And Error ◽  
Significance Level ◽  
Individual Bioequivalence ◽  
Alternative Approach ◽  
Within Subjects ◽  
Log Ratio ◽  
Selection Of

Cascading With Inner Systems: Hankel Singular Values and Characteristic Values

2020 ◽  
Vol 65 (2) ◽  
pp. 727-732
Author(s):  
Arturo Buscarino ◽  
Luigi Fortuna ◽  
Mattia Frasca ◽  
Giuseppe Nunnari
Keyword(s):  
Singular Values ◽  
Hankel Singular Values ◽  
Characteristic Values
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