A Self-Organizing Incremental Spatiotemporal Associative Memory Networks Model for Problems with Hidden State

The identifying history sequences for <svg height="15.2701pt" id="M610" style="vertical-align:-3.834pt" version="1.1" viewbox="-0.0498162 -11.4361 11.0876 15.2701" width="11.0876pt" 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="M445 282C445 390 384 448 297 448C266 448 231 437 189 418C96 376 23 279 23 151C23 65 66 -12 169 -12C233 -12 294 18 337 53C411 113 445 201 445 282ZM355 280C355 161 302 62 243 36C231 31 219 30 207 30C147 30 111 78 111 154C111 302 180 380 220 399C231 404 246 407 264 407C311 407 355 367 355 280Z" id="g113-112"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="468" vert-adv-y="468"></glyph.data></g><g transform="matrix(.0091,0,0,-0.0091,6.084,-5.741)"><path d="M310 541L304 571C290 586 211 619 185 610L80 76L131 52L310 541Z" id="g50-31"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="361" vert-adv-y="361"></glyph.data></g><g transform="matrix(.0091,0,0,-0.0091,6.019,3.784)"><path d="M389 0V32C297 38 291 46 291 118V635C234 613 175 595 109 583V556L161 554C203 552 207 547 207 497V118C207 46 201 38 110 32V0H389Z" id="g50-50"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="487" vert-adv-y="487"></glyph.data></g></svg> and <svg height="15.2701pt" id="M611" style="vertical-align:-3.834pt" version="1.1" viewbox="-0.0498162 -11.4361 13.0528 15.2701" width="13.0528pt" 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="M445 282C445 390 384 448 297 448C266 448 231 437 189 418C96 376 23 279 23 151C23 65 66 -12 169 -12C233 -12 294 18 337 53C411 113 445 201 445 282ZM355 280C355 161 302 62 243 36C231 31 219 30 207 30C147 30 111 78 111 154C111 302 180 380 220 399C231 404 246 407 264 407C311 407 355 367 355 280Z" id="g113-112"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="468" vert-adv-y="468"></glyph.data></g><g transform="matrix(.0091,0,0,-0.0091,6.084,-5.741)"><path d="M310 541L304 571C290 586 211 619 185 610L80 76L131 52L310 541Z" id="g50-31"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="361" vert-adv-y="361"></glyph.data></g><g transform="matrix(.0091,0,0,-0.0091,9.123,-5.741)"><path d="M310 541L304 571C290 586 211 619 185 610L80 76L131 52L310 541Z" id="g50-31"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="361" vert-adv-y="361"></glyph.data></g><g transform="matrix(.0091,0,0,-0.0091,6.019,3.784)"><path d="M389 0V32C297 38 291 46 291 118V635C234 613 175 595 109 583V556L161 554C203 552 207 547 207 497V118C207 46 201 38 110 32V0H389Z" id="g50-50"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="487" vert-adv-y="487"></glyph.data></g></svg>.

Computational Intelligence and Neuroscience

tab1

Table 1

Table 1: A Self-Organizing Incremental Spatiotemporal Associative Memory Networks Model for Problems with Hidden State 