Development of Real Time Multitask Kernel

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

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

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Multitask Multiple Kernel Learning

We present a general regularization-based framework for Multi-task learning (MTL), in which the similarity between tasks can be learned or refined using `pnorm Multiple Kernel learning (MKL). Based on this very general formulation (including a general loss function), we derive the corresponding dual formulation using Fenchel duality applied to Hermitian matrices. We show that numerous establish...

متن کامل

Real - Time Kernel for

D’nia is a real-time system and cross-development environment based on Oberon. It is used for the programming and control of embedded, mechatronic systems. Until now, it was available for various VME boards based on the MC680x0 processor. The main goal of this work was the development of a real-time kernel for the PowerPC family of RISC processors, allowing D’nia to run on this new hardware. Th...

متن کامل

The Asterix real-time kernel

This paper describes a real-time kernel, Asterix, that in a practical manner makes use of many of the recent advances made in the real-time systems research community. The basic ambition behind the development of the Asterix real-time kernel was to pack state-of the art research results into package such that it can be easily used and understood by people in the embedded systems industry. From ...

متن کامل

Editorial : Real - Time Kernel Interfacesbyprof

Current real-time kernels present inadequate, incomplete, and missing functionality in their interfaces. As a result of these poor interfaces, real-time systems are diicult to design, maintain, analyze, and understand. Here, I present examples of the poor interfaces and suggest improvements for scheduling, memory management, and interprocess communication. Basically , I am suggesting a need for...

متن کامل

Multitask Learning Using Regularized Multiple Kernel Learning

Empirical success of kernel-based learning algorithms is very much dependent on the kernel function used. Instead of using a single fixed kernel function, multiple kernel learning (MKL) algorithms learn a combination of different kernel functions in order to obtain a similarity measure that better matches the underlying problem. We study multitask learning (MTL) problems and formulate a novel M...

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

ژورنال

عنوان ژورنال: Journal of Applied Sciences

سال: 2008

ISSN: 1812-5654

DOI: 10.3923/jas.2008.3083.3095