Analyzing the Formation of Structure inHigh - Dimensional Self - Organizing Maps RevealsDi erences to Feature Map

نویسندگان

  • Maximilian Riesenhuber
  • Hans-Ulrich Bauer
  • Theo Geisel
چکیده

We present a method for calculating phase diagrams for the high-dimensional variant of the Self-Organizing Map (SOM). The method requires only an ansatz for the tesselation of the data space induced by the map, not for the explicit state of the map. Using this method we analyze two recently proposed models for the development of orientation and ocular dominance column maps. The phase transition condition for the orientation map turns out to be of diierent form than of the corresponding low-dimensional map.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Steel Consumption Forecasting Using Nonlinear Pattern Recognition Model Based on Self-Organizing Maps

Steel consumption is a critical factor affecting pricing decisions and a key element to achieve sustainable industrial development. Forecasting future trends of steel consumption based on analysis of nonlinear patterns using artificial intelligence (AI) techniques is the main purpose of this paper. Because there are several features affecting target variable which make the analysis of relations...

متن کامل

Analyzing the Formation of Structure in High-Dimensional Self-Organizing Maps Reveals Differences to Feature Map Models

We present a method for calculating phase diagrams for the high dimensional variant of the Self Organizing Map SOM The method requires only an ansatz for the tesselation of the data space induced by the map not for the explicit state of the map Using this method we analyze two recently proposed models for the development of orientation and ocular dominance column maps The phase transition condi...

متن کامل

Landforms identification using neural network-self organizing map and SRTM data

During an 11 days mission in February 2000 the Shuttle Radar Topography Mission (SRTM) collected data over 80% of the Earth's land surface, for all areas between 60 degrees N and 56 degrees S latitude. Since SRTM data became available, many studies utilized them for application in topography and morphometric landscape analysis. Exploiting SRTM data for recognition and extraction of topographic ...

متن کامل

Development and Spatial Structure of Cortical Feature Maps: A Model Study

Feature selective cells in the primary visual cortex of several species are organized in hierarchical topographic maps of stimulus features like "position in visual space", "orientation" and" ocular dominance". In order to understand and describe their spatial structure and their development, we investigate a self-organizing neural network model based on the feature map algorithm. The model exp...

متن کامل

Controling the Magniication Factor of Self-organizing Feature Maps

The magniication exponents occuring in adaptive map formation algorithms like Kohonen's self-organizing feature map deviate for the information theoretically optimal value = 1 as well as from the values which optimize, e.g., the mean square distortion error (= 1=3 for one-dimensional maps). At the same time, models for categorical perception such as the \perceptual magnet" eeect which are based...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007