Environmental Engineering Reference
In-Depth Information
B.3.1 Biharmonic approximation of neural models
In Chapter 6, Section 6.2 , we presented an approximated representation of Eq. ( B.12 ),
based on a Taylor expansion of the integral term in the neighborhood of
φ = φ 0 (i.e.,
for small values of z ). If the kernel function has axial symmetry and only the terms
up to the fourth order are retained, Eq. ( B.12 ) can be approximated as ( Murray , 2002 )
∂φ
2
4
t
f (
φ
)
+ ω 0 (
φ φ 0 )
+ ω 2
φ + ω 4
φ,
(B.19)
where the terms on the right-hand-side are the same as in Eq. ( 6.2 )and
w m is the
m th-order moment of the kernel function defined in Eq. ( 6.3 ). In the case of axial
symmetric kernel functions, the odd-order moments of
( z ) are zero.
It can be shown that a second-order expansion (i.e., a Fisher equation) is unable to
lead to persistent patterns (e.g., Murray , 2002 ) and that the biharmonic term
ω
4
φ
is needed in the series expansion to obtain [with approximation ( B.19 )] deterministic
patterns that do not vanish with time. In fact, linear-stability analysis of the state
φ = φ
ω
4
0 with respect to a perturbation ˆ
e γ t + i k · r leads to the dispersion relation:
φ
( r
,
t )
f (
ω 2 k 2
ω 4 k 4
γ
( k )
=
φ 0 )
+ ω 0
2
+
4
.
(B.20)
0), the most unstable mode
k max is zero and no patterns emerge. In the case of biharmonic approximation ( B.19 )
(i.e., when
In the absence of the biharmonic term (i.e., when
ω
=
4
ω
=
0), th e most unstable mode can be easily obtained from Eq. ( B.20 )
4
5 ω
=
.
as k max
0
4 . Patterns emerge when k max is real and different from zero (i.e.,
2
ω 2 and
ω 4 need to have the same sign), and
γ
>
( k max )
0:
2
2
ω
f (
γ
( k max )
=
φ 0 )
+ ω 0
ω 4 >
0
.
(B.21)
4
φ = φ 0 in the absence of spatial dynamics requires f (
In addition, the stability of
φ 0 )
to be negative, as in the first of conditions ( B.16 ). Moreover, in many applications
φ
is
always nonnegative. This condition is met when
ω 0 <
0. Because in this case
ω 0 and
f (
φ 0 ) are both negative, Eq. ( B.21 ), combined with the requirement that
ω 2 and
ω 4
have the same sign, implies that pattern formation occurs only if
ω 2 and
ω 4 are also
negative. However, the condition that
ω 4 are negative is only necessary
and not sufficient for pattern formation as condition ( B.21 ) would still need to be met
for the instability to emerge.
ω 0 ,
ω 2 ,and
B.4 Patterns emerging from differential-flow instability
The third major deterministic model of self-organized pattern formation associ-
ated with symmetry-breaking instability is due to differential flow. This mechanism
 
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