The Lyapunov stability of the model depends on length feedback.

Slides:



Advertisements
Similar presentations
Aim: How do we find the zeros of polynomial functions?
Advertisements

Rotational Motion.
Linearisation about point equilibrium n-dimensional autonomous a constant / point equilibrium solution of the dynamics a ‘neighbouring’ solution first-order.
Finite Difference Methods to Solve the Wave Equation To develop the governing equation, Sum the Forces The Wave Equation Equations of Motion.
Section 8.3 – Systems of Linear Equations - Determinants Using Determinants to Solve Systems of Equations A determinant is a value that is obtained from.
like a spider hanging out Powerpoint deck using every slide background pattern foreground black background white box transition from right 2.5 second.
Spatial Lotka-Volterra Systems Joe Wildenberg Department of Physics, University of Wisconsin Madison, Wisconsin USA.
Holt CA Algebra 1 Copyright © by Holt, Rinehart and Winston. All Rights Reserved. Simplify the expression. (2a 2 b 3 c 5 )(4ab 2 c 4 ) A. B. C. D. Week.
Solving polynomial equations
Warm-up 1.What are the different ways to solve quadratic equation? Solve the following problem by completing the square.
2.1 – Linear and Quadratic Equations Linear Equations.
Copyright © 2012 Pearson Education, Inc. Publishing as Addison Wesley R.5 The Basics of Equation Solving  Solve linear equations.  Solve quadratic equations.
Modeling interactions 1. Pendulum m – mass R – rod length x – angle of elevation Small angles x.
Standard form of an equation means we write an equation based on its exponents. 1.Arrange the terms so that the largest exponent comes first, then the.
Section 2-5 Zeros of Polynomial Functions. 1. Find all the zeros of and write the polynomial as a product of linear factors.
Solving Linear Systems
1. Write the equation in standard form.
Revenue = (# of Calculators ) * ( price )
Linear Inequalities in Two Variables
Matrix Inverse and Condition
Distribution of the amount of corticosterone in five primary feathers of bald eagles sampled in 21 mm segments from distal to proximal position along the.
PIECEWISE FUNCTIONS.
Students will be able to calculate and interpret inverse variation.
Topics in Phase-Space Jeffrey Eldred
Factoring (3.2.2) December 10th, 2016.
Quadratic Patterns.
Techniques for studying correlation and covariance structure
Equation Review Given in class 10/4/13.
Factor and Solve Polynomial Equations Lesson 2.4
Parent Functions.
Variations in the composition of mottle patterns.
Review: Simplify.
Parent Functions.
3.4 – The Quadratic Formula
LIAL HORNSBY SCHNEIDER
Unit 1 Representing Real Numbers
Equation Review.
Algebra 2 Ch.6 Notes Page 40 P Polynomials and Linear Functions.
Distribution of the differences in smallest worthwhile effects (SWEs) of land-based and water-based pulmonary rehabilitation on 6-min walk distance (in.
Horizontal plane projections of the endpoint force response to perturbations in several directions. Horizontal plane projections of the endpoint force.
The direction of the endpoint motion producing maximum response for each muscle was calculated from the linearized state equations for the model. The direction.
Solving a System of Linear Equations
Breathing motion of myoglobin: the superposed Mb structures before laser illumination (orange) and after 750 min of laser illumination (yellow) at 140.
The curvature and total bending predicted for biorobotic fin ray 4 (152 mm in length) in seven different fin ray models. The curvature and total bending.
Flexural rigidity measured for the biological fin rays (points), scaled 1000 times, and fitted by models of fin rays (lines; see text for discussion of.
Positive relationship between the residual breaking force and cuticle area of lamellar joints. Positive relationship between the residual breaking force.
Linear relationship between the measured rate of blood flow to the systemic circuit () and rate of blood flow through the left aorta () at 0, 12 and 24 h.
Effect of 20E on locomotion behavior.
Swimming paths of Freja in no fish (A) and fish trials (B) with no eyecups and when blindfolded (with eyecups). Swimming paths of Freja in no fish (A)
Estimates of the kinematics of the medio-lateral widths of the I3 muscle during biting using the three-dimensional kinematic model. Estimates of the kinematics.
Relationship between plastron length and (A) the amount of antibodies that can bind to lipopolysaccharide (LPS), (B) avidity, (C) total immunoglobulin,
Frequency and source level analysis of Amazon river dolphin echolocation clicks. Frequency and source level analysis of Amazon river dolphin echolocation.
(A) Counterclockwise contour Γ around a crack tip showing an element of path length ds, with unit vector n normal to the path and with stress and displacement.
Examples of the different position of the centre of head rotation (CR)
Mean CO2 release rates (μmol CO2 h–1; averaged across all individuals tested) at normoxia as a function of mean fresh mass (mg; log–log plot) for tenebrionid.
Effect of chronic disturbance and acute stressor on testosterone levels. Effect of chronic disturbance and acute stressor on testosterone levels. (A) Testosterone.
Strategic Communications at TRIUMF
(A) Mean maximum single-jaw forces (± s.d.), by species.
Graphical representation of the three different models used to estimate the rate of oxygen consumption V̇O2 from heart rate fh in a hypothetical arriving.
Kinematic measurements recorded as squid approached shrimp and fish.
Resilience (R) as a function of frequency at amplitudes of 0
The schematic of formation of vortex ring T1.
Leeches require closed loop sensory feedback to localize stimuli.
Phylogenetic analysis of AquK2P.
Mean CO2 release rates (averaged across all individuals tested) versus PO2 for each species of (A) tenebrionid and (B) scarabaeid. Mean CO2 release rates.
Incidence of childhood type 1 diabetes in Western Australia from 1985 through Incidence of childhood type 1 diabetes in Western Australia from 1985.
(A) Mean swim speed (±s. d
Effect of cocaine on locomotion.
Flow field adjacent to an eel (body length L=0
Revenue = (# of Calculators ) * ( price )
Presentation transcript:

The Lyapunov stability of the model depends on length feedback. The Lyapunov stability of the model depends on length feedback. The distribution of the largest real component of the eigenvalues (λmax) of the linearized equations of motion is shown across 10,000 activation patterns. The value of λmax is greater than zero for all 10,000 activation patterns in the model without length feedback (black square) and less than zero for all 10,000 activation patterns in the model with length feedback (white square). Also shown is the perturbation halving/doubling time (t50). Nathan E. Bunderson et al. J Exp Biol 2010;213:2131-2141 © 2010.