Global Stability, Bifurcation, and Chaos Control in a Delayed Neural Network Model

<div>Solution trajectory showing (a) asymptotic stable behavior when <svg height="12.1266pt" id="M125" style="vertical-align:-3.42784pt" version="1.1" viewbox="-0.0498162 -8.69876 105.485 12.1266" width="105.485pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><path d="M548 455L523 469C505 448 490 439 461 439C416 439 374 447 316 447C144 447 23 310 23 161C23 47 89 -12 179 -12C312 -12 429 106 429 244C429 303 419 344 368 386L371 388C404 383 440 378 474 378C507 378 530 411 548 455ZM350 274C350 191 308 25 198 25C144 25 108 75 108 157C108 264 170 395 276 395C296 395 320 384 333 360C347 334 350 316 350 274Z" id="g113-240"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="565" vert-adv-y="565"></glyph.data></g><g transform="matrix(.0135,0,0,-0.0135,11.442,0)"><path d="M535 323V373H52V323H535ZM535 138V188H52V138H535Z" id="g117-34"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="587" 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Advances in Artificial Neural Systems

fig6

Figure 6

Figure 6: Global Stability, Bifurcation, and Chaos Control in a Delayed Neural Network Model 