Mitchell, T. J. (2010) An exploration of evolutionary computation ...

More documents

Recommendations

Info

An Exploration of Evolutionary Computation Applied to Frequency Modulation Audio Synthesis Parameter Optimisation Thomas James Mitchell A thesis submitted in partial fulfilment of the requirements of the University of the West of England, Bristol for the degree of Doctor of Philosophy Bristol Institute of Technology, Faculty of Environment and Technology, University of the West of England, Bristol May 2010
Acknowledgments With so many people to thank who have indirectly contributed to this work I would first like to acknowledge those whose names are not mentioned here: family, friends – if you have ever said ―you‘re still doing that?‖ then you know who you are – I am forever indebted. I would principally like to thank my director of studies Professor Tony Pipe who has been an endless source of inspiration and confidence from start to finish. Additionally, I would like to thank my other supervisors: Dr David Creasey, Dr Marcus Lynch and Stephen Allen whose contributions have been invaluable, especially in the drafting of this thesis. I would also like to thank Professor Alan Winfield for providing a forceful boot onto the path and also for providing funding in desperate times. I would also like to thank the Engineering and Physical Sciences Research Council for providing me with the opportunity to learn about all this stuff. Finally, I would also like to express my gratitude to Dr Johnson Abraham, Dr Azarhar Machwe and Bhuvan Sharma for their friendship, company, humour and lengthy discussion on this mission; Professor Ian Parmee for the space; Professor Eduardo Miranda, Professor David Corne and Professor Larry Bull for reading and examining this thesis; Dr Charlie Sullivan for his help and ideas; Mike Bollen and Georgina Caldwell for their time proof reading ―the tale of the derandomised mutation operator‖; Rob Brown for sharing the pain; and to all the inspirational people who have demonstrated what drive, focus and dynamic thinking can achieve. i
Page 1: Mitchell, T. J. (2010) An explorati
Page 5 and 6: Abstract With the ever-increasing c
Page 7 and 8: 4 A Clustering-Based Niching Evolut
Page 9 and 10: 7.7.1.3 Contrived Matching with Tim
Page 11 and 12: 5.10: Mean and 95% confidence inter
Page 13 and 14: List of Tables 4.1: MTQ function pa
Page 15 and 16: To experimental musicians lacking t
Page 17 and 18: 1.1.2 Frequency Modulation Audio Sy
Page 19 and 20: The Bessel functions for are shown
Page 21 and 22: 1.3 Contributions In satisfying the
Page 23 and 24: Chapter 2 Background: Evolutionary
Page 25 and 26: Figure 2.1: The evolutionary model
Page 27 and 28: 2.3 Canonical Evolutionary Algorith
Page 29 and 30: it position (locus) may be absent o
Page 31 and 32: t = 0; initialise P μ(t); loop beg
Page 33 and 34: When The benefit of (intermediate)
Page 35 and 36: sphere, or hypersphere, dependent u
Page 37 and 38: the rule may only be applied when a
Page 39 and 40: Firstly, there is no guarantee that
Page 41 and 42: As the research field of evolutiona
Page 43 and 44: five of this thesis are based. The
Page 45 and 46: sparsely throughout the search spac
Page 47 and 48: Selection Pressure - The rate at wh
Page 49 and 50: enable the formation of species, it
Page 51 and 52: 3.4.1.2 Restricted Tournament selec
Page 53 and 54:
over the landscape, and the dilutin
Page 55 and 56:
Species 1 Genus Figure 3.2: Meta-ES
Page 57 and 58:
diffusion model, on the other hand,
Page 59 and 60:
fitness Niche Centre Figure 3.4: Ni
Page 61 and 62:
also applied within each subpopulat
Page 63 and 64:
outperformed by a simple GA. A seco
Page 65 and 66:
4.1 The Fuzzy Clustering Evolution
Page 67 and 68:
membership to each cluster. In prac
Page 69 and 70:
Fuzzy Intermediate Recombination -
Page 71 and 72:
Parents are subsequently merged and
Page 73 and 74:
4.2.3 New Recombination Operators T
Page 75 and 76:
Global - the ability of the algorit
Page 77 and 78:
period in which all sub-populations
Page 79 and 80:
4.3.2.1 Experiments on the Multimod
Page 81 and 82:
Discussion The canonical ES variant
Page 83 and 84:
Results (20+140) / CES / discrete /
Page 85 and 86:
function. The parameters for the fi
Page 87 and 88:
Discussion The results acquired fro
Page 89 and 90:
these experiments as the quantity o
Page 91 and 92:
Performance Criteria In assessing t
Page 93 and 94:
discrete recombination is employed;
Page 95 and 96:
Figure 4.15: Mean and 95% confidenc
Page 97 and 98:
Discussion These results corroborat
Page 99 and 100:
Figure 4.19: Mean and 95% confidenc
Page 101 and 102:
partitioned into five clusters, the
Page 103 and 104:
However, the question arises as to
Page 105 and 106:
The most consistent finding of Wieg
Page 107 and 108:
Wiegand demonstrated that a pseudo-
Page 109 and 110:
accurate approximation of an interv
Page 111 and 112:
cooperating subpopulation into mult
Page 113 and 114:
5.3.1.1 Collaboration One notable d
Page 115 and 116:
If one representative is selected f
Page 117 and 118:
The CCCES algorithm begins by initi
Page 119 and 120:
For the subsequent experiments, the
Page 121 and 122:
Discussion The results shown in tab
Page 123 and 124:
Figure 5.7: Maximum-fitness curve f
Page 125 and 126:
dimensional multimodal function wit
Page 127 and 128:
From the results shown in Table 5.3
Page 129 and 130:
that, as the dimensionality of the
Page 131 and 132:
only a moderate increase in fitness
Page 133 and 134:
It is interesting that the results
Page 135 and 136:
Niching - it is desirable that mult
Page 137 and 138:
6.2 Synthesiser Choice Since the fo
Page 139 and 140:
Modulating Oscillators Carrier Osci
Page 141 and 142:
6.4 Sound Synthesis Applications of
Page 143 and 144:
with results again presented using
Page 145 and 146:
employed by commercial synthesis ma
Page 147 and 148:
While these metrics are able to suc
Page 149 and 150:
Unlike the metrics considered in se
Page 151 and 152:
Figure 6.6 provides a plot of the l
Page 153 and 154:
6.5 Summary of this Chapter In this
Page 155 and 156:
constant spectral form as static to
Page 157 and 158:
Figure 7.2a represents the most fun
Page 159 and 160:
7.3 Evolutionary Matching Synthesis
Page 161 and 162:
If the frame size is assigned a pow
Page 163 and 164:
an exhaustive search yields no bett
Page 165 and 166:
CCES, in which each dimension of th
Page 167 and 168:
7.6.1.1 Contrived Matching with Sin
Page 169 and 170:
elative spectral error ranged from
Page 171 and 172:
the second, where the parameters fo
Page 173 and 174:
Discussion Figure 7.8: Mean and 95%
Page 175 and 176:
and relative spectrum error is exam
Page 177 and 178:
The flat spectrum produced by the a
Page 179 and 180:
Matching Model Single Simple FM Dou
Page 181 and 182:
Acoustic Target Matching Results Fi
Page 183 and 184:
Figure 7.17: Muted trumpet tone (to
Page 185 and 186:
Performance Criteria As before, res
Page 187 and 188:
indicated the discreet recombinatio
Page 189 and 190:
7.7.1.3 Contrived Matching with Tim
Page 191 and 192:
(a): Target sound time waveform (b)
Page 193 and 194:
Matching Model Single Simple FM Dou
Page 195 and 196:
Algorithmic Parameters Oboe Target
Page 197 and 198:
The frequency spectrograms are plot
Page 199 and 200:
Frequency (Hz) Frequency (Hz) Frequ
Page 201 and 202:
Amplitude (dB) Amplitude (dB) Figur
Page 203 and 204:
Chapter 8 Listening Tests Despite t
Page 205 and 206:
Amplitude (dB) Amplitude (dB) Ampli
Page 207 and 208:
Listening Test One - Similarity Ran
Page 209 and 210:
frequency harmonics well but the mi
Page 211 and 212:
Listening Test Two - General Sound
Page 213 and 214:
Figure 8.6c: Listening test two ins
Page 215 and 216:
The FM sound produced by the matchi
Page 217 and 218:
Frequency (Hz) Amplitude four descr
Page 219 and 220:
Frequency (Hz) Amplitude (a) Violin
Page 221 and 222:
capabilities of the triple simple F
Page 223 and 224:
Chapter 9 Conclusions and Further W
Page 225 and 226:
environments. It was shown that the
Page 227 and 228:
Also included in chapter seven, was
Page 229 and 230:
matching algorithm to probe the und
Page 231 and 232:
The author hopes that this work goe
Page 233 and 234:
Bäck, T., and Schutz, M. (1996) In
Page 235 and 236:
Chowning, J. M. (1973) The synthesi
Page 237 and 238:
Eshelman, L. J. (1990) The CHC Adap
Page 239 and 240:
Hanagandi, V. and Nikolaou, M. (199
Page 241 and 242:
Huband, S., Hingston, P., While L.
Page 243 and 244:
Lim, S. M. and B. T. G. Tan. (1999)
Page 245 and 246:
Miller, B. L., and Goldberg, D. E.
Page 247 and 248:
Popovici, E. and De Jong, K. (2005)
Page 249 and 250:
Rudolph, G (1991) Global Optimizati
Page 251 and 252:
Tan, B. T. G. and S. M. Lim, (1996)
Page 253 and 254:
Wiegand, R. P., and Sarma, J. (2004
Page 255:
Appendix 1 - Listening Test 1 - Res
show all

Mitchell, T. J. (2010) An exploration of evolutionary computation ...

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?