Global Stability Analysis of Neural Networks with Constant Time Delay via Frobenius Norm

<div>System solution for the initial state <span class="nowrap"><svg height="12.7178pt" id="M247" style="vertical-align:-3.42947pt" version="1.1" viewbox="-0.0498162 -9.28833 130.426 12.7178" width="130.426pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M556 393C556 426 537 448 514 448C496 448 478 435 471 420C468 414 462 401 466 394C473 382 480 368 480 346C480 268 392 143 338 67H336C329 163 319 253 309 330S286 448 254 448C215 448 160 383 127 337L143 311C167 344 200 373 208 373S222 365 229 320C246 214 264 66 268 -20C219 -83 131 -171 17 -239L25 -261L137 -235C248 -110 273 -79 335 8C384 77 481 215 520 287C544 332 556 363 556 393Z"></path></g><g transform="matrix(.013,0,0,-0.013,7.529,0)"><path d="M300 -147C201 -63 143 98 143 270S200 602 300 686L282 710C136 610 70 450 70 271V270C70 89 136 -72 282 -170L300 -147Z"></path></g><g transform="matrix(.013,0,0,-0.013,12.027,0)"><path d="M241 635C89 635 35 457 35 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Mathematical Problems in Engineering

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Figure 1

Figure 1: Global Stability Analysis of Neural Networks with Constant Time Delay via Frobenius Norm 