## 7 Use Case 1: CNN for Damage Location Regression and Classification
## Appendix A Appendix A.1 Abbreviations

Act Activation and transfer function (using floating point arithmetic) Discretized and scaled activation function for fixed-point integer arithmetic FooFP Discretized and scaled Model for integer arithmetic Foo Floating point model Forth Stack-based programming language with reverse polish notation GWW Guided Ultrasonic Waves (Lamb wave) MLISA Machine Learning Instruction Set Architecture REXA Real-time capable and Extensible Architecture SHM Structural Health Monitoring VM Virtual Machine
```
**Algorithm A.2** _MLISA Code_
```
(Layer 1 input ) arrayxL0128 (Layer 2 conv ) arrayxL1N0124 arrayylLN1124 arrayylLN2124 arrayylLN3124 arrayylL1 (1129...(3) ) arrayWL1N0 (1299...(4) ) arrayWL1N1 (-5119...(4) ) arrayWL1N2 (2334..(4) ) arrayWL1N3 (-4736..(4) ) ( Layer 3 relu ) ( Layer 4 pool ) arrayYL3N0162 arrayyl3N162 arrayYL3N262 arrayYL3N362 array als124 ( Layer 5 conv ) arrayYL4N006... arrayPL4 (1159...(3) ) arrayal4S06 arrayal4S160 arrayal4S260 arrayal4S360 arrayWL4N0S0 (-750...(2) )...... ( Layer 8 fc ) arrayYL716 arraybL7 { 939..(15) } arrayLT7S016 arrayaL7S116 arrayalT8216 arrayaL7S216 arrayaL7S316 arrayWL7N0S0 (-407..(29) )... ( Layer 9 tanh ) ( Layer 10 fc ) arrayYL98 arraybL9 { 103...(7) } arrayWL9 { 3962..(127) } ( Layer 11 tanh ) ( Layer 12 fc ) arrayJL112 2 arraybL11 (-355..(1) ) arrayWL11 {-1915..(15) } ( Layer 13 regression ) : forward ( Layer 1 input ) ( Layer 2 conv ) xL0 vL1N0 yL1N0 -5000 128 5 1 0 vecconv xL0 wL1N1 yL1N1 -5000 128 5 1 0 vecconv xL0 wL1N2 yL1N2 -5000 128 5 1 0 vecconv xL0 wL1N3 yL1N3 -5000 128 5 1 0 vecconv ( Layer 3 relu ) yL1N0 yL1N0 $ relu 0 vecmap... ( Layer 4 pool ) yL2N0 1 aL3 -5000 124 -2 2 0 vecconv  aL3 l aL3 -5000 124 -2 2 0 vecconv  aL3 l aL3 -5000 124 -2 2 0 vecconv  aL3 l aL3 -5000 124 -2 2 0 vecconv  aL3 l aL3 -5000 124 -2 2 0 vecconv  aL3 l aL3 -5000 124 -2 2 0 vecconv  aL3 l yL3N1 -5000 124 -2 2 0 vecconv... ( Layer 5 conv ) yL3N0 wL4N0S0 aL4S0 -5000 62 3 1 0 vecconv  yL3N1 wL4N0S1 aL4S1 -5000 62 3 1 0 vecconv  yL3N2 wL4N0S2 aL4S2 -5000 62 3 1 0 vecconv  yL3N3 wL4N0S3 aL4S3 -5000 62 3 1 0 vecconv
```
**Algorithm A.2** _MLISA Code_
```
(Layer 1 input ) arrayxL0128 (Layer 2 conv ) arrayxL1N0124 arrayylLN124 arrayylLN3124 arrayylLN3124 arrayylL1129...(3)  arrayWL1N0 (1299...(4) ) arrayWL1N1 (-5119...(4) ) arrayWL1N2 (-5119...(4) ) arrayWL1N2 (-5119...(4) ) arrayWL1N3 (-5119.
```
aL480 aL481 aL482 aL483 yL4N004 vecsum... (Layer6 relu) yL4N0 yL4N0 yL4N0 yL4N0 yL4N00 vecmap... (Layer7 pool) yL5N01 aL6-500060-220 vecconv aL61 aL6-500060-220 vecconv aL61 aL6-500060-220 vecconv aL61 yL6N0-500060-220 vecconv... (Layer8 fc) yL6N01 aL7N0N0S0 vecfold yL6N1 aL7N18N7N0S10 vecfold yL6N2 aL7S2 wL7N0S20 vecfold yL6N3 aL7S3 wL7N0S30 vecfold aL7S0 aL7S1 aL7S2 aL7S3 yL7N00-50004 vecsum... (Layer9 tanh) yL7 yL7 yL7s tanh0 vecmap (Layer10 fc) yL8 yL9 sL9-5000 vecfold yL9 yL9 sD10 vecad (Layer11 tanh) yL9 yL9 stanh0 vecmap (Layer12 fc) yL10 yL1 wL11-5000 vecfold yL11 yL11 bL10 vecadd yL11 yL11 bL10 vecadd (Layer13 regression) ;
```
**Algorithm A1**_Cont.
```
arrayxL01 arrayyL14 arraybL1[-281..(3)]arraywL1[-1875..(3)]arrayyL38 arraybL3[-1016..(7)]arraywL3[1537..(31)]arrayyL54 arrayyL54 arraybL5[701..(3)]arraywL5[324..(31)]arrayyL71 - arraybL7[-655..(0)]arraywL7[-906..(3)] : forward xL0 yL1 wL1-5000 vecfold yL1 yL1 bL10 vecad yL1 yL1 yL1 yL1 stanh0 vecmap yL2 yL3 wL3-500 vecfold yL3 yL3 bL30 vecad yL3 yL3 yL3$tanh0 vecmap yL4 yL5 wL5-5000 vecfold yL5 yL5 yL5 bL500 vecad yL5 yL5 yL5 yL5$tanh0 vecmap yL6 yL7 wL7-5000 vecfold yL7 yL7 yL7 bL70 vecadd ;
```
**Algorithm A2**MLSA code of discretized Poly4 ANN model
``` arrayxL01 arrayyL14 arraybL1[-281..(3)]arraywL1[-1875..(3)]arrayyL38 arraybL3[-1016..(7)]arraywL3[1537..(31)]arrayyL54 arraybL5[701..(3)]arraywL5[324..(31)]arrayyL71 - arraybL7[-655..(0)]arraywL7[-906..(3)]arraywL7[-906..(3)]arraywL7[-106  
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