13th International Conference on Membrane Computing - MTA Sztaki

More documents

Recommendations

Info

A. Obtu̷lowicz The arcs (links) from the peripherical nodes of each cluster to the central node of the original cluster (in Fig. 3(c)) are compressed to the arcs between non-elementary membranes (in Fig. 3(d)) corresponding to the clusters. The skin membrane (root) is omitted in Fig. 3(d). References 1. Alexander, Ch., A city is not a tree, reprint from the magazine Design No. 206 (1966), Council of Industrial Design. 2. Baas, N. B., Emmeche, C., On Emergence and Explanation, Intellectica 2, no. 25 (1997), pp. 67–83. 3. Bailly, F., Longo, G., Objective and Epistemic Complexity in Biology, invited lecture, <strong>International</strong> <strong>Conference</strong> on Theoretical Neurobiology, New Delhi, February 2003, http://www.di.ens.fr/users/longo 4. Barr, F., Welles, Ch., Category Theory for Computing Science, Prentice–Hall, New York 1990; second edition 1993. 5. Barrière, L., et al., Deterministic hierarchical networks, submitted to Networks, 2006. 6. Domshlak, C., On recursively directed hypercubes, Electron. J. Combin. 9 (2002), #R23. 7. Ehresmann, A. C., Vanbremeersch, J.-P., Multiplicity Principle and Emergence in Memory Evolutive Systems, SAMS vol. 26 (1996), pp. 81–117. 8. Ehresmann, A. C., Vanbremeersch, J.-P., Consciousness as Structural and Temporal Integration of the Context, http://perso.orange.fr/vbm-ehr/Ang/W24A7.htm 9. Ehresmann, A. C., Vanbremeersch, J.-P., Memory Evolutive Systems. Studies in Multidisciplinarity vol. 4, Elsevier, Amsterdam, 2007. 10. Eroni, S., Harel, D., Cohen, I. R., Toward Rigorous Comprehension of Biological Complexity: Modeling, Execution, and Visualization of Thymic T-Cell Maturation, Genome Research 13 (2003), pp. 2485–2497. 11. Felleman, D. J., Van Essen, D. C., Distributed hierarchical processing in the primate cerebral cortex, Cerebral Cortex 1 (1991), No. 1, pp. 1–47. 12. Fukushima, K., Neocognitron: A hierarchical neural network capable of visual pattern recognition, Neural Networks 1 (1988), No. 2, pp. 119–130. 13. Fukushima, K., Neocognitron trained with winner-kill-loser rule, Neural Networks 23 (2010), pp. 926–938. 14. Harel, D., On Visual Formalisms, Comm. ACM 31 (1988), pp. 514–530. 15. Inseberg, A., Parallel Coordinates: Visual Multidimensional Geometry and its Applications, Springer-Verlag, Berlin 2008. 16. Lair, Ch., Elements de la theorie des Patchworks, Diagrammes 29 (1993). 17. Membrane computing web page http://ppage.psystems.eu 18. Obtu̷lowicz, A., Multigraphical membrane systems: a visual formalism for modeling complex systems in biology and evolving neural networks, in: Preproceedings of Workshop of Membrane Computing, Thessaloniki 2007, pp. 509–512. 19. Ovchinnikov, S., Partial cubes: characterizations and constructions, Discrete Mathematics 308 (2008), pp. 5597–5621. 20. Păun, Gh., Membrane Computing. An Introduction, Springer-Verlag, Berlin 2002. 21. Ravasz, E., Barabási, A.-L., Hierarchical organization in complex networks, Physical Review E 67 (2003), 026112. 348
Multigraphical membrane systems revisited 22. Reisenhuber, M., Poggio, T., Hierarchical models of object recognition in cortex, Nature Neuroscience 11 (1999), pp. 1019–1025. 23. Seitz, Ch. L., The cosmic cube, Comm. ACM 28 (1985), pp. 22–33. 24. Shin, Sun-Joo, The Logical Status of Diagrams, Cambridge 1994. 25. Thiel, T., The design of the connection machine, Design Issues 10 (1994), pp. 5–18; see also http://www.mission-base.com/tamiko/theory/cm_txts/di-frames.html 26. Van Essen, D. C., Maunsell, J. H. R., Hierarchical organization and functional streams in the virtual cortex, Trends in NeuroScience, September 1983, pp. 370–375. 27. von der Malsburg, Ch., Binding in Models of Perception and Brain Function, Current Opinions in Neurobiology 5 (1995), pp. 520–526. 28. von der Malsburg, Ch., The What and Why of Binding: The Modeler’s Perspective, Neuron 95–104 (1999), pp. 94–125. 349
Page 1:
Erzsébet Csuhaj-Varjú Marian Gheo
Page 4 and 5:
Editors Erzsébet Csuhaj-Varjú Dep
Page 6 and 7:
Preface In addition to the texts or
Page 8 and 9:
Contents M.A. Martínez-del-Amor, I
Page 11 and 12:
13th Inter
Page 13 and 14:
(Tissue) P systems with decaying ob
Page 15 and 16:
Page 17 and 18:
Page 19 and 20:
Page 21 and 22:
Page 23 and 24:
Page 25 and 26:
Page 27 and 28:
Page 29 and 30:
Page 31 and 32:
Page 33 and 34:
Page 35:
Page 38 and 39:
Sorin Istrail, Solomon Marcus of pr
Page 40 and 41:
Sorin Istrail, Solomon Marcus proba
Page 42 and 43:
Sorin Istrail, Solomon Marcus stati
Page 44 and 45:
Sorin Istrail, Solomon Marcus 4.
Page 46 and 47:
Sorin Istrail, Solomon Marcus his f
Page 49 and 50:
13th Inter
Page 51 and 52:
Turing’s three pioneering initiat
Page 53 and 54:
Turing’s three pioneering initiat
Page 55 and 56:
13th Inter
Page 57:
MP systems for systems biology tere
Page 60 and 61:
Yu. Rogozhin this obstacle and to g
Page 62 and 63:
Yu. Rogozhin 10. J. Cocke, M. Minsk
Page 64 and 65:
M. Stannett The question arises, wh
Page 67:
Regular Contributions
Page 70 and 71:
T. Ahmed, G. DeLancy, A. Paun almos
Page 72 and 73:
T. Ahmed, G. DeLancy, A. Paun purpo
Page 74 and 75:
T. Ahmed, G. DeLancy, A. Paun Fig.
Page 76 and 77:
T. Ahmed, G. DeLancy, A. Paun gener
Page 78 and 79:
T. Ahmed, G. DeLancy, A. Paun
Page 80 and 81:
T. Ahmed, G. DeLancy, A. Paun Table
Page 82 and 83:
T. Ahmed, G. DeLancy, A. Paun 14. H
Page 84 and 85:
T. Ahmed, G. DeLancy, A. Paun 84
Page 87 and 88:
13th Inter
Page 89 and 90:
Asynchronuous and maximally paralle
Page 91 and 92:
Page 93 and 94:
Page 95 and 96:
Page 97:
Page 100 and 101:
A. Alhazov, R. Freund, H. Heikenwä
Page 102 and 103:
Page 104 and 105:
Page 106 and 107:
Page 108 and 109:
Page 110 and 111:
Page 112 and 113:
Page 114 and 115:
Page 116 and 117:
A. Alhazov, Yu. Rogozhin With coope
Page 118 and 119:
A. Alhazov, Yu. Rogozhin 2.3 P Syst
Page 120 and 121:
A. Alhazov, Yu. Rogozhin Such a sys
Page 122 and 123:
A. Alhazov, Yu. Rogozhin applied, f
Page 124 and 125:
A. Alhazov, Yu. Rogozhin - one extr
Page 126 and 127:
B. Aman, G. Ciobanu formalisms is e
Page 128 and 129:
B. Aman, G. Ciobanu membranes appea
Page 130 and 131:
B. Aman, G. Ciobanu • [ ] recep r
Page 132 and 133:
B. Aman, G. Ciobanu Definition 3. A
Page 134 and 135:
B. Aman, G. Ciobanu { w i , for all
Page 136 and 137:
B. Aman, G. Ciobanu The four transi
Page 138 and 139:
B. Aman, G. Ciobanu A state space i
Page 140 and 141:
B. Aman, G. Ciobanu to reiterate th
Page 143 and 144:
13th Inter
Page 145 and 146:
On structures and behaviors of spik
Page 147 and 148:
Page 149 and 150:
Page 151 and 152:
Page 153 and 154:
Page 155 and 156:
Page 157 and 158:
Page 159:
Page 162 and 163:
L. Cienciala, L. Ciencialová, M. P
Page 164 and 165:
Page 166 and 167:
Page 168 and 169:
Page 170 and 171:
Page 172 and 173:
H. ElGindy, R. Nicolescu, H. Wu pat
Page 174 and 175:
H. ElGindy, R. Nicolescu, H. Wu pro
Page 176 and 177:
H. ElGindy, R. Nicolescu, H. Wu (b)
Page 178 and 179:
H. ElGindy, R. Nicolescu, H. Wu 8 r
Page 180 and 181:
H. ElGindy, R. Nicolescu, H. Wu Pse
Page 182 and 183:
H. ElGindy, R. Nicolescu, H. Wu to
Page 184 and 185:
H. ElGindy, R. Nicolescu, H. Wu ter
Page 186 and 187:
H. ElGindy, R. Nicolescu, H. Wu 4.
Page 188 and 189:
H. ElGindy, R. Nicolescu, H. Wu Tab
Page 190 and 191:
Page 192 and 193:
H. ElGindy, R. Nicolescu, H. Wu 6 R
Page 194 and 195:
H. ElGindy, R. Nicolescu, H. Wu (wh
Page 196 and 197:
Page 199 and 200:
13th Inter
Page 201 and 202:
A formal framework for P systems wi
Page 203 and 204:
Page 205 and 206:
Page 207 and 208:
Page 209 and 210:
Page 211 and 212:
13th Inter
Page 213 and 214:
A new approach for solving SAT by P
Page 215 and 216:
Page 217 and 218:
Page 219 and 220:
Page 221 and 222:
13th Inter
Page 223 and 224:
Maintenance of chronobiological inf
Page 225 and 226:
Page 227 and 228:
Page 229 and 230:
Page 231 and 232:
4 3.5 3 2.5 2 1.5 1 0.5 0 0 50 100
Page 233 and 234:
Page 235 and 236:
Page 237 and 238:
Page 239 and 240:
Page 241 and 242:
Page 243 and 244:
13th Inter
Page 245 and 246:
Using a kernel P system to solve th
Page 247 and 248:
Page 249 and 250:
Page 251 and 252:
Page 253 and 254:
Page 255 and 256:
Page 257 and 258:
Page 259 and 260:
13th Inter
Page 261 and 262:
Spiking neural P systems with funct
Page 263 and 264:
Page 265 and 266:
Page 267 and 268:
Page 269 and 270:
Page 271 and 272:
Page 273 and 274:
Page 275:
Page 278 and 279:
L.F. Macías-Ramos, M.J. Pérez-Jim
Page 280 and 281:
Page 282 and 283:
Page 284 and 285:
Page 286 and 287:
Page 288 and 289:
Page 290 and 291:
Page 292 and 293:
M.A. Martínez-del-Amor, I. Pérez-
Page 294 and 295:
Page 296 and 297:
Page 298 and 299: M.A. Martínez-del-Amor, I. Pérez-
Page 311 and 312: 13th Inter
Page 313 and 314: Membranes with local environments A
Page 315 and 316: Membranes with local environments T
Page 317 and 318: Membranes with local environments -
Page 319 and 320: Membranes with local environments -
Page 321 and 322: Membranes with local environments I
Page 325 and 326: On efficient algorithms for SAT dis
Page 327 and 328: On efficient algorithms for SAT 2 S
Page 329 and 330: On efficient algorithms for SAT 2.4
Page 331 and 332: On efficient algorithms for SAT inc
Page 333 and 334: On efficient algorithms for SAT •
Page 335 and 336: On efficient algorithms for SAT Not
Page 337 and 338: On efficient algorithms for SAT the
Page 339: On efficient algorithms for SAT 32.
Page 342 and 343: A. Obtu̷lowicz - its underlying tr
Page 344 and 345: A. Obtu̷lowicz 2−ramification
Page 346 and 347: A. Obtu̷lowicz The correctness of
Page 353 and 354: An analysis of correlative and quan
Page 371 and 372: Sublinear-space P systems with acti
Page 387 and 388: Modelling ecological systems with t
Page 399 and 400:
Modelling ecological systems with t
Page 401 and 402:
Page 403 and 404:
Page 405:
Page 408 and 409:
D. Sburlan hence one can gather use
Page 410 and 411:
D. Sburlan represents a 0L system.
Page 412 and 413:
D. Sburlan assuming that M is in a
Page 414 and 415:
D. Sburlan q 1 {t−, T 1 ↓, T 2
Page 416 and 417:
D. Sburlan In case of M, the states
Page 418 and 419:
D. Sburlan We introduced a formal s
Page 420 and 421:
P. Sosík [9, 10], several research
Page 422 and 423:
P. Sosík The rules of a system lik
Page 424 and 425:
P. Sosík 1. The family Π is polyn
Page 426 and 427:
P. Sosík (a) subsequently and recu
Page 428 and 429:
P. Sosík contentFinal = content(l,
Page 430 and 431:
P. Sosík Hence, with the aid of th
Page 432 and 433:
P. Sosík 8. Lakshmanan K. and Rama
Page 434 and 435:
S. Verlan, J. Quiros more relevance
Page 436 and 437:
S. Verlan, J. Quiros For a regular
Page 438 and 439:
S. Verlan, J. Quiros digital FPGA c
Page 440 and 441:
S. Verlan, J. Quiros where k j = N
Page 442 and 443:
S. Verlan, J. Quiros Now let us con
Page 444 and 445:
S. Verlan, J. Quiros We consider a
Page 446 and 447:
S. Verlan, J. Quiros the present co
Page 448 and 449:
S. Verlan, J. Quiros Table 2 gives
Page 450 and 451:
S. Verlan, J. Quiros Using similar
Page 452 and 453:
S. Verlan, J. Quiros 5. M. Maliţa,
Page 455 and 456:
13th Inter
Page 457 and 458:
Simplifying Event-B models of P sys
Page 461:
Author Index Adorna H., 143 Agrigor
show all

13th International Conference on Membrane Computing - MTA Sztaki

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

Delete template?

Save as template?