Entropy,
Год журнала:
2024,
Номер
26(10), С. 855 - 855
Опубликована: Окт. 10, 2024
In
the
past
two
decades,
research
in
field
of
chaotic
synchronization
has
attracted
extensive
attention
from
scholars,
and
at
same
time,
more
methods,
such
as
master-slave
synchronization,
projection
sliding
film
fractional-order
so
on,
have
been
proposed
applied
to
secure
communication.
this
paper,
based
on
radial
basis
function
neural
network
theory
particle
swarm
optimisation
algorithm,
RBFNN-PSO
synchronisation
method
is
for
Sprott
B
system
with
external
noise.
The
RBFNN
controller
constructed,
its
parameters
are
used
parameters,
optimal
values
obtained
by
PSO
training
method,
which
overcomes
influence
noise
achieves
system.
Then,
it
shown
numerical
simulation
analysis
that
scheme
a
good
performance
against
Because
multiple
attractors
richer
dynamics,
chaos
image
encryption
particular,
Zigzag
disambiguation
top
corner
rotation
RGB
channel
selection
proposed,
sequences
diffused
disambiguated
data
streams,
respectively.
Therefore,
decryption
transmission
implemented
results
given,
random
distribution
characteristics
encrypted
images
analysed
using
histogram
Shannon
entropy
final
achieve
expected
results.
Symmetry,
Год журнала:
2025,
Номер
17(1), С. 143 - 143
Опубликована: Янв. 18, 2025
Memristives
provide
a
high
degree
of
non-linearity
to
the
model.
This
property
has
led
many
studies
focusing
on
developing
memristive
models
more
non-linearity.
article
novel
fractional
discrete
system
with
incommensurate
orders
using
ϑi-th
Caputo-like
operator.
Bifurcation,
phase
portraits
and
computation
maximum
Lyapunov
Exponent
(LEmax)
are
used
demonstrate
their
impact
system’s
dynamics.
Furthermore,
we
employ
sample
entropy
approach
(SampEn),
C0
complexity
0-1
test
quantify
validate
chaos
in
system.
Studies
indicate
that
manifests
diverse
dynamical
behaviors,
including
hidden
chaos,
symmetry,
asymmetry
attractors,
which
influenced
by
derivative
values.
Moreover,
2D
non-linear
controller
is
presented
stabilize
synchronize
The
work
results
provided
numerical
simulation
obtained
MATLAB
R2024a
codes.
Fractal and Fractional,
Год журнала:
2024,
Номер
8(11), С. 628 - 628
Опубликована: Окт. 24, 2024
Memristors
have
become
important
components
in
artificial
synapses
due
to
their
ability
emulate
the
information
transmission
and
memory
functions
of
biological
synapses.
Unlike
counterparts,
which
adjust
synaptic
weights,
memristor-based
operate
by
altering
conductance
or
resistance,
making
them
useful
for
enhancing
processing
capacity
storage
capabilities
neural
networks.
When
integrated
into
systems
like
Hopfield
networks,
memristors
enable
study
complex
dynamic
behaviors,
such
as
chaos
multistability.
Moreover,
fractional
calculus
is
significant
model
effects,
enabling
more
accurate
simulations
systems.
Fractional-order
particular,
exhibit
chaotic
multistable
behaviors
not
found
integer-order
models.
By
combining
with
fractional-order
these
offer
possibility
investigating
different
phenomena
This
investigates
dynamical
behavior
a
network
(HNN)
incorporating
memristor
piecewise
segment
function
one
its
synapses,
highlighting
impact
derivatives
memristive
on
stability,
robustness,
complexity
system.
Using
four
neurons
case
study,
it
demonstrated
that
HNN
exhibits
multistability,
coexisting
attractors,
limit
cycles.
Through
spectral
entropy
analysis,
regions
initial
condition
space
display
varying
degrees
are
mapped,
those
areas
where
series
approach
pseudo-random
sequence
numbers.
Finally,
proposed
implemented
Field-Programmable
Gate
Array
(FPGA),
demonstrating
feasibility
real-time
hardware
realization.
Mathematics,
Год журнала:
2025,
Номер
13(2), С. 182 - 182
Опубликована: Янв. 8, 2025
The
widespread
distribution
of
medical
images
in
smart
healthcare
systems
will
cause
privacy
concerns.
unauthorized
sharing
decrypted
remains
uncontrollable,
though
image
encryption
can
discourage
disclosure.
This
research
proposes
a
double-level
security
scheme
for
to
overcome
this
problem.
proposed
joint
and
watermarking
is
based
on
singular-value
decomposition
(SVD)
chaotic
maps.
First,
three
different
random
sequences
are
used
encrypt
the
LL
subband
discrete
wavelet
transform
(DWT)
domain;
then,
HL
LH
sub-bands
embedded
with
watermark
information;
end,
we
obtain
watermarked
encrypted
inverse
DWT
(IDWT)
transform.
In
study,
SVD
domain.
main
originality
that
decryption
extraction
be
performed
separately.
Experimental
results
demonstrate
superiority
method
key
spaces
(10225),
PSNR
(76.2543),
UACI
(0.3329).
implementation,
following
achievements
attained.
our
meet
requests
levels.
Second,
Third,
detected
Thus,
experiment
analysis
effectiveness
scheme.
Chaos An Interdisciplinary Journal of Nonlinear Science,
Год журнала:
2025,
Номер
35(2)
Опубликована: Фев. 1, 2025
Investigating
the
dynamics
of
neural
networks
under
electromagnetic
induction
contributes
to
understanding
complex
electrical
activity
in
brain.
This
paper
proposes
a
memristive
chain
Hopfield
network
(MCHNN)
containing
unidirectional
synaptic
connections,
where
flux-controlled
memristor
mimics
between
neurons.
Under
different
parameters,
equilibria
MCHNN
have
numbers
and
properties,
thus
producing
diverse
dynamics.
Numerical
analysis
shows
that
there
are
coexisting
attractors,
such
as
point
attractors
periodic
chaotic
which
yielded
from
initial
conditions.
Moreover,
memristor’s
internal
parameter
can
be
considered
special
signal
controller.
It
acts
on
oscillation
amplitude
neuron’s
output
signal,
along
with
control
offset-boosting
about
flux.
By
building
feasible
hardware
platform,
numerical
outcomes
supported,
existence
proposed
is
verified.
In
addition,
NIST
test
indicate
has
good
pseudo-randomness
suitable
for
engineering
applications.
Electronics,
Год журнала:
2025,
Номер
14(4), С. 766 - 766
Опубликована: Фев. 16, 2025
Locally
active
memristors
with
an
Edge-of-Chaos
kernel
(EOCK)
represent
a
significant
advancement
in
the
simulation
of
neuromorphic
dynamics.
However,
current
research
on
EOCK
remains
at
circuit
level,
without
further
analysis
their
feasibility.
In
this
context,
we
designed
memristor
and
installed
it
third-order
circuit,
where
showed
local
activity
stability
under
defined
voltage
inductance
parameters.
This
behavior
ensured
that
by
varying
input
inductance,
could
effectively
simulate
various
neural
activities,
including
inhibitory
postsynaptic
potential
chaotic
waveforms.
By
subsequently
integrating
into
Hopfield
network
(HNN)
framework
substituting
self-coupling
weight,
observed
rich
spectrum
dynamic
behaviors,
rare
phenomenon
antimonotonicity
bubble
bifurcation.
Finally,
used
hardware
circuits
to
realize
these
generated
phenomena,
confirming
feasibility
memristor.
introducing
HNN
studying
its
implementation,
study
provides
theoretical
insights
empirical
basis
for
developing
systems
replicate
complexity
human
brain
functions.
reference
development
application
future.
