Neural Network Simulation Environments
Josef Skrzypek
2012년 12월 · The Springer International Series in Engineering and Computer Science 254권 · Springer Science & Business Media
5.0star
리뷰 1개report
eBook
251
페이지
report검증되지 않은 평점과 리뷰입니다. 자세히 알아보기
eBook 정보
Neural Network Simulation Environments describes some of the best examples of neural simulation environments.
All current neural simulation tools can be classified into four overlapping categories of increasing sophistication in software engineering. The least sophisticated are undocumented and dedicated programs, developed to solve just one specific problem; these tools cannot easily be used by the larger community and have not been included in this volume. The next category is a collection of custom-made programs, some perhaps borrowed from other application domains, and organized into libraries, sometimes with a rudimentary user interface. More recently, very sophisticated programs started to appear that integrate advanced graphical user interface and other data analysis tools. These are frequently dedicated to just one neural architecture/algorithm as, for example, three layers of interconnected artificial `neurons' learning to generalize input vectors using a backpropagation algorithm. Currently, the most sophisticated simulation tools are complete, system-level environments, incorporating the most advanced concepts in software engineering that can support experimentation and model development of a wide range of neural networks. These environments include sophisticated graphical user interfaces as well as an array of tools for analysis, manipulation and visualization of neural data.
Neural Network Simulation Environments is an excellent reference for researchers in both academia and industry, and can be used as a text for advanced courses on the subject.
All current neural simulation tools can be classified into four overlapping categories of increasing sophistication in software engineering. The least sophisticated are undocumented and dedicated programs, developed to solve just one specific problem; these tools cannot easily be used by the larger community and have not been included in this volume. The next category is a collection of custom-made programs, some perhaps borrowed from other application domains, and organized into libraries, sometimes with a rudimentary user interface. More recently, very sophisticated programs started to appear that integrate advanced graphical user interface and other data analysis tools. These are frequently dedicated to just one neural architecture/algorithm as, for example, three layers of interconnected artificial `neurons' learning to generalize input vectors using a backpropagation algorithm. Currently, the most sophisticated simulation tools are complete, system-level environments, incorporating the most advanced concepts in software engineering that can support experimentation and model development of a wide range of neural networks. These environments include sophisticated graphical user interfaces as well as an array of tools for analysis, manipulation and visualization of neural data.
Neural Network Simulation Environments is an excellent reference for researchers in both academia and industry, and can be used as a text for advanced courses on the subject.
평점 및 리뷰
5.0
리뷰 1개
이 eBook 평가
의견을 알려주세요.
읽기 정보
스마트폰 및 태블릿
노트북 및 컴퓨터
컴퓨터의 웹브라우저를 사용하여 Google Play에서 구매한 오디오북을 들을 수 있습니다.
eReader 및 기타 기기
Kobo eReader 등의 eBook 리더기에서 읽으려면 파일을 다운로드하여 기기로 전송해야 합니다. 지원되는 eBook 리더기로 파일을 전송하려면 고객센터에서 자세한 안내를 따르세요.
