Next:
Basic operations for managing
Up:
Neural Data Analysis User's
Previous:
Basics of data management
Contents
User's reference
Subsections
Basic operations for managing the name space
Managing directories
Listing names in the name space
Removing name entries
Renaming name entries
Copying data frames or fields
Displaying the contents of data frames and fields
Querying the vector lenght of a name entry
Setting the contents of a data field
Selecting fields into a data frame
Selecting classes to a classified data frame
Selecting items to frames
Attaching a data frame to the end of another
Handling classified data frames
Creating a data field as a number series
Converting fields of a data frame into a string field
Conversion routines for time
Matrices
The matrix structure
Older matrix conversion commands
New matrix conversion commands
Singular Value Decomposition
Calculation of the pseudo-inverse matrix
Calculation of the LU decomposition
Sum of two matrices
Substraction of two matrices
Multiplication of two matrices
Multiplication of a matrix by a number
Transpose of a matrix
Calculate matrix inverse
Cholesky decomposition
Data reorganization
Transposing a data frame
Joining data frames
Indexing through a joining operation
Finding unique data records
Finding unique indexes from classes
Finding the indexes of a classified data from another classified data
Merging a grouping and a classified data
Set-relational operations for classes
Convert a classification into a field
Converting SOM classification to location codes
Combining classifications
Converting sum values into propabilities
Binarizing a classification to data fields
Picking data records based on a classified data
Sorting a data frame
Classifying a data frame with a BMU classifier
Classifying data records to sequences
Concatenating sequences
Overlapping sequential data sets
Compacting self-similar data
Changing field types
Basic computing operations
Preprocessing data
Basic preprocessing
Whitening preprocessor command
Equalize values within records
Treatment for missing data
Generating data
Creating orthogonal DoE plan for two level factors
Field evaluator
Expressions
Field calculator
Record selector
Classification with expressions
Select classes by evaluating a boolean expression
Record evaluator
Class evaluator
Field statistics
Basic statistics for fields
Quartiles for data fields
Histograms for fields
Comparison of two data frames
Class statistics
Basic statistics for classes
Class identifiers
Identifying classes by values
Evaluating the number of items in classes
Values for distributions in classes
Histograms for classes
Fuzzy sets
Creating a fuzzy structure
Creating fuzzy sets
Altering the membership functions of fuzzy sets
An example sequence of fuzzy operations
Computing fuzzy membership values for a field
Calculating distances between data records
Group membership evaluation
Distributions
Calculating the percentiles of the
-distribution (level of confidence)
The inverse of the
-distribution function
Calculating the
-distribution function and its inverse
Calculating the univariate normal cumulative distribution function (uncdf) and its inverse function
Calculating the multivariate normal cumulative distribution function (mvncdf)
Algorithms
The Tree-Structured Self-Organizing Map and related structures
Training a TS-SOM
Classifying data by a TS-SOM
Smoothing data in a TS-SOM
Creating a field for TS-SOM layer information
Storing the indexes of neurons into a data frame
Getting and setting data in a TS-SOM layer
Computing a U-matrix
Spreading the groups of core neurons
Mapping data records onto a TS-SOM
Generating data according to the grid of a TS-SOM
Backpropagation
The basic learning rule
The basic learning rule with a momentum term
Global adaptive training step length
The Matlab neural network toolbox style training
The Silva & Almeida training
The RPROP training
The Levenberg-Marquard training
Importing a new data to a trained network
Visualizing an MLP network
Searching for MLP inputs to match given outputs
MLP neural network with one hidden layer
Stochastic and batch learning
Rprop learning
MLP network outputs calculation
Classical scaling and Sammon's mapping
Scaling a data set using the principal component analysis (PCA)
Linear regression and confidence bands
Data clustering
Hierarchical clustering
k-means clustering
Fuzzy c-means clustering
Image processing
File commands
Image conversions and cropping
Conversions between images and data frames
Converting graphs into pixel data frames
Creating an image mosaic according to a SOM
Basic filtering and thresholding
Histograms
Edge and line detection methods
Edge detection
Line detection
Extracting features from an image
General global features
Finding top and bottom points from an image
Connecting points with neighbours
Cutting connections in a graph
Features from graphs
BLOB analysis methods
Calculating feature distributions based on blobs
Calculating features based on blobs
Finding blobs with certain properties
Fourier commands
Commands related to fuzzy-analysis
Shape analysis
Calculation of size of centroid
Calculation of Bookstein coordinates of shape
Calculation of full Procrustes fit (superimposition) of one shape to another
Centering of landmarks' coordinates of shape
Revised image processing commands
General and I/O commands
Conversion commands
Pixel-level commands
Fourier transform for grayscale images
Morphological operations for binary images
Co-occurence matrix commands
Segmentation commands
Stochastic geometry commands
Simulation commands
Graph commands
Fractal commands
Graphics
Creating and initializing graphic structures
Creating a graphic structure and connecting a frame to it
Managing subgraphs
Setting a structure over subgraphs
Setting the visualized layer
Setting the topology and child links of TS-SOM
Creating trajectories
Connecting neurons
Creating contours
The U-matrix presentation
Axis for each dimension - x, y and z
3D scatterplotting
Setting the graphical contents of subgraphs
Setting the locations of neurons in 3D
Setting the shape of the neurons
Setting the size of neurons
Setting the proportional diameters of circular neurons
Setting the colors or gray levels of neurons
The visibility of the neurons
Graphical presentations inside subgraphs
Axes in subgraphs
Plotting data in subgraphs
Bars in subgraphs
Range plots in subgraphs
Line diagrams in subgraphs
Line diagrams based on the values of the field
Histograms in subgraphs
The curves of the functions
Field labels and values as text in subgraphs
Record labels in subgraphs
Data matrix in subgraphs
Vector fields
Colors and scaling
Graphics for groups in a SOM
Adding custom graphic elements
Defining custom graphic texts
Defining custom graphic polygons
Defining custom graphic ellipses
Setting a viewpoint to a graphic image in 3D
Displaying an image in a window
Displaying graphics
Querying the settings of a graphic structure
Saving the settings of a graphic structure into a file
Graphic frames
Creating a graphic frame
Adding a graphic structure to a graphic frame
Setting the places of graphic structures within graphic frames
Commands for working with low level images
Generating a low level image from a graphic structure
Finding objects from a graphic structure
Executing macros according to a selection within a graphic structure
Generating a low level image for a graphic frame (tech.)
Updating a graphic structure
File I/O
Loading data structures from a file
Saving data structures into a file
PostScript printing
Executing command files
Device I/O
Image acquisition and camera handling
Viewing live camera image
Snap images from cameras
Querying and altering camera settings
Stopping an ethernet server program
Data Acquisition
Starting data acquisition
Stopping data acquisition
Engel Monitoring System
Initializing EMS communication
Using EMS to collect data
Using EMS to change machine settings
Communicating with devices using SCL
Waiting for events to occur
Miscellaneous commands
Changing current filesystem directory
Conditional execution
Command echo and messaging
Logging commands into a file
Getting help
Error tolerance
Returning from a macro
Leaving NDAshell
Checking host operating system type
Running a UNIX command from the NDAshell
Initializing the random number generator
Commands related to graphical user interfaces
Opening a graphic tool
Opening a graphical fuzzy tool
Viewing a graph using OpenGL
Pausing the execution of a command file
Updating a graphic window from the command line
OS filesystem commands
Get current working directory
Set current working directory
Create a new directory
Remove an existing directory
Copy an existing file to another location
Copy files to another location
Remove an existing file
Remove existing files
List files and directories
List directories
List files
Undocumented commands
Data and SOM operations
Image operations
Textual data processing
Probabilistic calculation
Socket communication
Anssi Lensu 2006-02-23
-distribution (level of confidence)
-distribution function
-distribution function and its inverse