This book reports on the latest advances in concepts and further development of principal component analysis (PCA), discussing in detail a number of open problems related to dimensional reduction techniques and their extensions. It brings together research findings, previously scattered throughout many scientific journal papers worldwide, and presents them in a methodologically unified form. Offering vital insights into the subject matter in self-contained chapters that balance the theory and concrete applications, and focusing on open problems, it is essential reading for all researchers and practitioners with an interest in PCA
A Principal Components Analysis (PCA) based algorithm is used to drive a 16 DoF underactuated prosth...
A Principal Components Analysis (PCA) based algorithm is used to drive a 16 DoF underactuated prosth...
The article discusses selected problems related to both principal component analysis (PCA) and facto...
This book reports on the latest advances in concepts and further developments of principal component...
The principal component analysis (PCA) is a kind of algorithms in biometrics. It is a statistics tec...
Principal component analysis (PCA) is a tool able to transform data into a new space in which compon...
Principal Component Analysis (PCA from now on) is a multivariate data analysis technique used for ma...
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns ...
PCA (Principal Component Analysis ) are statistical techniques applied to a single set of variables ...
Principal Component Analysis (PCA) is a usual method in multivariate analysis to reduce data dimensi...
Principal Component Analysis (PCA from now on) is a multivariate data analysis technique used for ma...
Item does not contain fulltextHuman movements, recorded through kinematic data, can be described by ...
Human movements, recorded through kinematic data, can be described by means of principal component a...
Principal component analysis (PCA) is an exploratory statistical method for graphical description of...
In 1901, Karl Pearson invented Principal Component Analysis (PCA). Since then, PCA serves as a proto...
A Principal Components Analysis (PCA) based algorithm is used to drive a 16 DoF underactuated prosth...
A Principal Components Analysis (PCA) based algorithm is used to drive a 16 DoF underactuated prosth...
The article discusses selected problems related to both principal component analysis (PCA) and facto...
This book reports on the latest advances in concepts and further developments of principal component...
The principal component analysis (PCA) is a kind of algorithms in biometrics. It is a statistics tec...
Principal component analysis (PCA) is a tool able to transform data into a new space in which compon...
Principal Component Analysis (PCA from now on) is a multivariate data analysis technique used for ma...
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns ...
PCA (Principal Component Analysis ) are statistical techniques applied to a single set of variables ...
Principal Component Analysis (PCA) is a usual method in multivariate analysis to reduce data dimensi...
Principal Component Analysis (PCA from now on) is a multivariate data analysis technique used for ma...
Item does not contain fulltextHuman movements, recorded through kinematic data, can be described by ...
Human movements, recorded through kinematic data, can be described by means of principal component a...
Principal component analysis (PCA) is an exploratory statistical method for graphical description of...
In 1901, Karl Pearson invented Principal Component Analysis (PCA). Since then, PCA serves as a proto...
A Principal Components Analysis (PCA) based algorithm is used to drive a 16 DoF underactuated prosth...
A Principal Components Analysis (PCA) based algorithm is used to drive a 16 DoF underactuated prosth...
The article discusses selected problems related to both principal component analysis (PCA) and facto...