An unit cell of frequency selective surface is designed in order to control the transmission characteristic and reflection characteristic of electromagnetic wave for different application like Biomedical application, Waveguide Modulator, Ultra wide Band application, etc. Here a new FSS is proposed that consists of Polygon structure with circular slot loaded centrally. Polygon structure is used in order to increase the Bandwidth. This manuscript presents a comparative study of simulation oriented from ANSOFT based result and the result obtained from the Artificial Neural Network (ANN). To obtain good result proper training of neural network is required. Back Propagation Algorithm based on Gradient Decent (GD) method is used here for training of ANN. The result is in good agreement within the accepted error value.

1. EMPIRICAL STUDY OF ANN
BASED PREDICTION OF
RESONANT FREQUENCY AND
BANDWIDTH OF CIRCULAR SLOT
LOADED POLYGON FSS
AUTHOR NAME
• M. PANDA
• MD RABIUL HOSSAIN
• MD EHTESHAM HUSSAIN
• SAMRIDDHA SAMANTA
• RUBABA RAHMAN
Presented by
RUBABA RAHMAN

2. OUTLINE
 What is FSS
 Elements of FSS Design
 Types of FSS
 Applications of FSS.
 Work Done By The Candidate
 Conclusions

3. WHAT IS FREQUENCY SELECTIVE SURFACE ???
A frequency-selective surface (FSS) is any thin, repetitive
surface designed to reflect, transmit or absorb
electromagnetic fields based on frequency. In this sense, an
FSS is a type of optical filter or metal-mesh optical filters in
which the filtering is accomplished by virtue of the regular,
periodic pattern on the surface of the FSS.

4. ELEMENTS OF FSS DESIGN
Element Geometries:
Patch-type elements-capacitive effect.
Aperture-type element-Inductance Effect.

5. PATCH-TYPE ELEMENTS
The patch-array produces a capacitive response, Band Stop Filter

6. APERTURE-TYPE ELEMENT
Array of slots is inductive- Band Pass filter

7. TYPES OF FSS
FSS (Based on shapes by MUNK,[1])– 4 Classes.
1. The center
connected or
N-poles
2. The loop
Types
3. Solid
interiors or
plate types
4.Combinations
of 1,2,3

8. APPLICATIONS OF FREQUENCY SELECTIVE SURFACES ..
• Frequency selective surfaces have been most commonly used in
the radio frequency region of the electromagnetic spectrum
• use in applications as diverse as the aforementioned microwave
oven, antenna radomes and modern metamaterials.
• Sometimes frequency selective surfaces are referred to simply as
periodic surfaces and are a 2-dimensional analog of the new
periodic volumes known as photonic crystals.

9. ARTIFICIAL NEURAL NETWORK (ANN)
Artificial Neural Networks (ANNs) are a family of models inspired by biological
neural network i.e. the central nervous system of animals, in particular the brain
and are used to estimate or approximate functions that can depend on a large
number of inputs and are generally unknown. Artificial neural networks are
generally presented as systems of interconnected neurons which exchange
messages between each other. The connections have numeric weights that can
be tuned based on experience, making neural nets adaptive to inputs and
capable of learning.

10. PROPOSED STRUCTURE OF FSS
The geometry of the single layer FSS unit
cell structure shown in Fig which consists
of polygon with centrally circular slot
loaded. The dimension of unit cell
structure is clearly mentioned in the said
figure. For x, y direction periodicity the
length is 11mm & 16mm respectively.
The unit cells are placed in repeated
structure in 2D Array form
3 mm
10 mm3mm
12mm
11 mm
16mm

11. SIMULATION RESULT USING ANSOFT
Computer based extensive numerical method is used for designing the
parameter of FSS by using different commercial software. Numerical
methods are Finite Element Method (FEM), Method of Moment (MOM),
Finite Difference Time Domain (FDTD) method etc. For extensive simulation
ANSOFT simulation tool is adopted here.

12. BAND WIDTH VARIATION FOR DIFFERENT Y DIRECTION
PERIODICITY

13. RESONANT FREQUENCY FOR DIFFERENT Y DIRECTION
PERIODICITY

14. ARTIFICIAL ANN FOR PREDICTION OF BW AND RF
Back Propagation (BP) is best on MLN perception. Four layer
architecture is used here. One input layer, one output layer
and two hidden layer is used for the proposed ANN model.
For input layer of ANN model the periodicity in x-direction
and y-direction are taken. The output of ANN model is the
bandwidth and resonating frequency.

15. PROPOSE ANN MODEL FOR ESTIMATION OF BAND
WIDTH AND RESONANT FREQUENCY

16. DATA SEQUENCE FOR ANN
Sl no.
Periodici
ty in x-
direction
(mm)
Periodi
city in y-
direction
(mm)
1 11 18.5
2 11.5 17
3 12.5 17
4 13.5 18
5 14.5 19.5
Sl No.
ANSOFT
simulati
on B.W
(GHz)
ANN
B.W
(GHz)
1 4.63 4.75
2 5.49 5.38
3 5.28 5.4
4 4.38 4.28
5 3.53 3.66
Sl No.
ANSOFT
Simulati
on RF
(GHz)
ANN
RF(GHz)
1 10.35 10.43
2 10.17 10.27
3 9.98 10.1
4 9.88 9.76
5 9.62 9.57
INPUT Output for BW Output for RF

17. CONCLUSION
• All results are quite satisfactory.
• Results obtained by proposed ANN structure are compared with ANSOFT
simulation tool results.
• In both cases result are quite identical and error value is in acceptance range.
• For further future study authors intend to take new model with solid or slit
loaded structure with different dimensions.
• Apart from Neural Network authors concentrate on different types of soft
computing tool like PSO,GA, ant colony optimization.