Joint <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-6.1769pt" id="M1" height="17.5763pt" version="1.1" viewBox="-0.0657574 -11.3994 28.6941 17.5763" width="28.6941pt"><g transform="matrix(.017,0,0,-0.017,0,0)"><path id="g113-77" d="M541 160L512 170C485 116 462 88 439 67C411 41 376 35 318 35C272 35 238 37 224 48C207 61 205 85 212 121L290 533C305 611 308 615 391 622L397 650H139L133 622C217 615 221 612 206 533L126 118C111 41 103 34 23 26L17 0H474C489 31 528 124 541 160Z"/></g><g transform="matrix(.012,0,0,-0.012,10.948,4.134)"><path id="g50-50" d="M389 0V32C297 38 291 46 291 118V635C234 613 175 595 109 583V556L161 554C203 552 207 547 207 497V118C207 46 201 38 110 32V0H389Z"/></g><g transform="matrix(.012,0,0,-0.012,16.798,4.134)"><path id="g50-48" d="M381 704H317L48 -163H112L381 704Z"/></g><g transform="matrix(.012,0,0,-0.012,21.956,4.134)"><path id="g50-51" d="M414 144C384 79 371 75 317 75H135L276 221C367 316 408 376 408 465C408 570 327 635 237 635C179 635 131 609 100 575L42 494L67 471C94 510 138 565 205 565C277 565 321 517 321 435C321 348 258 270 195 195C146 137 88 81 33 26V0H411C423 44 433 88 446 135L414 144Z"/></g></svg>-Norm Constraint and Graph-Laplacian PCA Method for Feature Extraction

<div>The accuracy of different methods on simulation data with different numbers of samples.</div>

BioMed Research International

fig2

Figure 2

Figure 2: Joint <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-6.1769pt" id="M1" height="17.5763pt" version="1.1" viewBox="-0.0657574 -11.3994 28.6941 17.5763" width="28.6941pt"><g transform="matrix(.017,0,0,-0.017,0,0)"><path id="g113-77" d="M541 160L512 170C485 116 462 88 439 67C411 41 376 35 318 35C272 35 238 37 224 48C207 61 205 85 212 121L290 533C305 611 308 615 391 622L397 650H139L133 622C217 615 221 612 206 533L126 118C111 41 103 34 23 26L17 0H474C489 31 528 124 541 160Z"/></g><g transform="matrix(.012,0,0,-0.012,10.948,4.134)"><path id="g50-50" d="M389 0V32C297 38 291 46 291 118V635C234 613 175 595 109 583V556L161 554C203 552 207 547 207 497V118C207 46 201 38 110 32V0H389Z"/></g><g transform="matrix(.012,0,0,-0.012,16.798,4.134)"><path id="g50-48" d="M381 704H317L48 -163H112L381 704Z"/></g><g transform="matrix(.012,0,0,-0.012,21.956,4.134)"><path id="g50-51" d="M414 144C384 79 371 75 317 75H135L276 221C367 316 408 376 408 465C408 570 327 635 237 635C179 635 131 609 100 575L42 494L67 471C94 510 138 565 205 565C277 565 321 517 321 435C321 348 258 270 195 195C146 137 88 81 33 26V0H411C423 44 433 88 446 135L414 144Z"/></g></svg>-Norm Constraint and Graph-Laplacian PCA Method for Feature Extraction 

BioMed Research International

Joint -Norm Constraint and Graph-Laplacian PCA Method for Feature Extraction

Figure 2