Figure 1.
I-V characteristics of the considered memristor. (a) A = 1 V, 2 V, 3 V, 4 V and f = 1 Hz; (b) f = 1 Hz, 2 Hz, 3 Hz, 4 Hz and A = 4 V. The initial state ; (c) initial states: x0 = ±1, ±7, ±14, ±21, A = 4 V and f = 1 Hz.
Figure 1.
I-V characteristics of the considered memristor. (a) A = 1 V, 2 V, 3 V, 4 V and f = 1 Hz; (b) f = 1 Hz, 2 Hz, 3 Hz, 4 Hz and A = 4 V. The initial state ; (c) initial states: x0 = ±1, ±7, ±14, ±21, A = 4 V and f = 1 Hz.
Figure 2.
The designed multistable memristor synapse-based coupled bi-Hopfield neuron model.
Figure 2.
The designed multistable memristor synapse-based coupled bi-Hopfield neuron model.
Figure 3.
Determination of the equilibrium states and , which are indicated by the intersections of two function curves.
Figure 3.
Determination of the equilibrium states and , which are indicated by the intersections of two function curves.
Figure 4.
Influence of on the behaviors of the model: (a) bifurcation diagram (b) Lyapunov exponents for and .
Figure 4.
Influence of on the behaviors of the model: (a) bifurcation diagram (b) Lyapunov exponents for and .
Figure 5.
Phase spaces confirming the occurrence of chaos in the system for , and diverse selected values of : (a) period-1 for , (b) period-2 for , (c) period-3 for , (d) chaos for , (e) period-3 for , (f) period-6 for , (g) chaos for , (h) chaos for , (i) chaos for , (j) period-3 for , (k) period-6 for .
Figure 5.
Phase spaces confirming the occurrence of chaos in the system for , and diverse selected values of : (a) period-1 for , (b) period-2 for , (c) period-3 for , (d) chaos for , (e) period-3 for , (f) period-6 for , (g) chaos for , (h) chaos for , (i) chaos for , (j) period-3 for , (k) period-6 for .
Figure 6.
Impact of the initial state on the comportment of the model: (a) bifurcation diagram and (b) maximum Lyapunov exponent, for , , and .
Figure 6.
Impact of the initial state on the comportment of the model: (a) bifurcation diagram and (b) maximum Lyapunov exponent, for , , and .
Figure 7.
Several coexisting chaotic attractors at diverse positions for several value initial states with , , and .
Figure 7.
Several coexisting chaotic attractors at diverse positions for several value initial states with , , and .
Figure 8.
Cross section of the basin of attraction for , , and . Each domain of initial states leads to a color representing a particular phase space.
Figure 8.
Cross section of the basin of attraction for , , and . Each domain of initial states leads to a color representing a particular phase space.
Figure 9.
Implementation procedure of the elaborated multistable memristor synapse-based coupled bi-Hopfield neuron model.
Figure 9.
Implementation procedure of the elaborated multistable memristor synapse-based coupled bi-Hopfield neuron model.
Figure 10.
Hardware implementation devices. The dual-channel digital oscilloscope displays a chaotic attractor in the plane () for , , and .
Figure 10.
Hardware implementation devices. The dual-channel digital oscilloscope displays a chaotic attractor in the plane () for , , and .
Figure 11.
Phase portraits for and specific values of the coupling strength : (a) period-1 for , (b) period-2 for , (c) period-3 for , (d) chaos for , (e) period-3 for , (f) period-6 for , (g) chaos for , (h) chaos for , (i) chaos for , (j) period-3 for , (k) period-6 for , and .
Figure 11.
Phase portraits for and specific values of the coupling strength : (a) period-1 for , (b) period-2 for , (c) period-3 for , (d) chaos for , (e) period-3 for , (f) period-6 for , (g) chaos for , (h) chaos for , (i) chaos for , (j) period-3 for , (k) period-6 for , and .
Figure 12.
Complete diagram of the encryption algorithm.
Figure 12.
Complete diagram of the encryption algorithm.
Figure 13.
Numerical results: (a) initial image of cerebrovascular accident, (b) initial image of pulmonary fibrosis, (c) initial image of lung cancer, (d) encrypted image of cerebrovascular accident, (e) encrypted image of pulmonary fibrosis, (f) encrypted image of lung cancer, (g) decrypted image of cerebrovascular accident, (h) decrypted image of pulmonary fibrosis, (i) decrypted image of lung cancer.
Figure 13.
Numerical results: (a) initial image of cerebrovascular accident, (b) initial image of pulmonary fibrosis, (c) initial image of lung cancer, (d) encrypted image of cerebrovascular accident, (e) encrypted image of pulmonary fibrosis, (f) encrypted image of lung cancer, (g) decrypted image of cerebrovascular accident, (h) decrypted image of pulmonary fibrosis, (i) decrypted image of lung cancer.
Figure 14.
Results of slight key modification: (a) correct keys, (b) , (c) , (d) , (e) , and (f) .
Figure 14.
Results of slight key modification: (a) correct keys, (b) , (c) , (d) , (e) , and (f) .
Figure 15.
The distribution of the pixels of the unencrypted images (a), encrypted images (b), and decrypted images (c).
Figure 15.
The distribution of the pixels of the unencrypted images (a), encrypted images (b), and decrypted images (c).
Figure 16.
Impacts of external perturbations and information loss on the performances of the algorithm: (a1(i)–a1(iii)) encrypted images with , , and Gaussian noise, respectively. (a2(i)–a2(iii)) corresponding decrypted images. (b1(i)–b1(iii)) encrypted images with , , and salt and pepper noise, respectively. b2(i)–b2(iii) corresponding decrypted images. (c1(i)–c1(iii)) encrypted image with , , and information loss, respectively. (c2(i)–c2(iii)) corresponding decrypted images.
Figure 16.
Impacts of external perturbations and information loss on the performances of the algorithm: (a1(i)–a1(iii)) encrypted images with , , and Gaussian noise, respectively. (a2(i)–a2(iii)) corresponding decrypted images. (b1(i)–b1(iii)) encrypted images with , , and salt and pepper noise, respectively. b2(i)–b2(iii) corresponding decrypted images. (c1(i)–c1(iii)) encrypted image with , , and information loss, respectively. (c2(i)–c2(iii)) corresponding decrypted images.
Table 1.
A comparison of this work related to published ones.
Table 1.
A comparison of this work related to published ones.
References | Number of Neurons | Coexisting Attractors | Implementation | Applications |
---|
[8] | 3 | Yes | Pspice and DSP board | NA |
[9] | 4 | Yes | NA | Image encryption |
[10] | 3 | Yes | Hardware breadboard | NA |
[12] | 3 | Yes | PSIM simulation | NA |
[14] | 2 | Yes | PSIM circuit simulation | NA |
This work | 2 | Yes | Microcontroller | Biomedical image encryption |
Table 2.
Equilibria and their stability.
Table 2.
Equilibria and their stability.
ρ | γ | Equilibria | Eigenvalues | Stability |
---|
1 | 0.7 | | | Unstable saddle point (USP) |
| | Unstable saddle point (USP) |
Table 3.
NIST test results.
Table 3.
NIST test results.
Name of the Considered Test | p-Value | Test Results |
---|
x | y | z | |
---|
Frequency | 0.17360 | 0.50790 | 0.49918 | Validated |
Block-frequency | 0.18189 | 0.14409 | 0.18861 | Validated |
Runs | 0.96599 | 0.15381 | 0.21472 | Validated |
Longest runs of ones | 0.63350 | 0.65267 | 0.74264 | Validated |
Rank | 0.49885 | 0.49928 | 0.44669 | Validated |
DFT | 0.79219 | 0.30442 | 0.25890 | Validated |
No overlapping templates | 0.59850 | 0.07790 | 0.04530 | Validated |
Overlapping templates | 0.28548 | 0.37728 | 0.79657 | Validated |
Universal | 0.76180 | 0.99902 | 0.35890 | Validated |
Linear complexity | 0.79980 | 0.22241 | 0.94489 | Validated |
Serial test 1 | 0.81870 | 0.68489 | 0.22395 | Validated |
Serial test 2 | 0.34090 | 0.70814 | 0.11562 | Validated |
Approximate entropy | 0.43162 | 0.72734 | 0.61123 | Validated |
Cumulative sums (forward) | 0.26100 | 0.82875 | 0.45276 | Validated |
Random excursions x = 1 | 0.51045 | 0.57860 | 0.35246 | Validated |
Random excursions variant x = 1 | 0.96169 | 0.59897 | 0.84990 | Validated |
Table 4.
Information entropies of initial images and their corresponding encrypted versions.
Table 4.
Information entropies of initial images and their corresponding encrypted versions.
Entropy | Gray-Scale Images |
---|
Cerebrovascular Accident | Pulmonary Fibrosis | Lung Cancer |
---|
Initial image | 5.9029 | 7.3089 | 6.0119 |
Encrypted version | 7.9972 | 7.9974 | 7.9973 |
Table 5.
Computed correlation coefficients.
Table 5.
Computed correlation coefficients.
Direction | Gray-Scale Images |
---|
Initial Image | Encrypted Version |
---|
Cerebrovascular Accident | Pulmonary Fibrosis | Lung Cancer | Cerebrovascular Accident | Pulmonary Fibrosis | Lung Cancer |
---|
Horizontal | 0.9440 | 0.9923 | 0.9434 | 0.0048 | −0.0019 | −0.0024 |
Vertical | 0.9487 | 0.9927 | 0.9668 | 0.0022 | −0.0020 | −0.0034 |
Diagonal | 0.9004 | 0.9868 | 0.9255 | 0.0064 | −0.0026 | −0.0025 |
Average | 0.9310 | 0.9906 | 0.9452 | 0.0045 | −0.0022 | −0.0027 |
Table 6.
NPCR and UACI test results.
Table 6.
NPCR and UACI test results.
| Plaintext Sensitivity |
---|
Images | NPCR (%) | UACI (%) |
---|
Cerebrovascular accident | 99.6201 | 30.5290 |
Pulmonary fibrosis | 99.6094 | 28.3197 |
Lung cancer | 99.5773 | 33.3278 |
Table 7.
Comparison of this image encryption scheme with certain recent encryption methods.
Table 7.
Comparison of this image encryption scheme with certain recent encryption methods.
Algorithm | Entropy | Correlation Coefficients of Adjacent Pixels | NPCR (%) | UACI (%) |
---|
H | V | D |
---|
Our algorithm | 7.9971 | −0.0048 | 0.0034 | −0.0013 | 99.5651 | 30.6253 |
Ref. [35] | 7.8152 | 0.0692 | 0.0544 | 0.0396 | 96.42 | 27.35 |
Ref. [36] | 7.9964 | −0.0057 | −0.0034 | 0.0073 | 99.6185 | 33.6245 |
Ref. [37] | 7.9972 | −0.0245 | −0.0193 | −0.0226 | 99.60 | 28.62 |
Ref. [38] | 7.9969 | 0.0059 | 0.0016 | 0.0029 | 99.2172 | 33.4639 |