Sparse Matrix Implementation in Octave
نویسندگان
چکیده
This paper discusses the implementation of the sparse matrix support with Octave. It address the algorithms that have been used, their implementation, including examples of using sparse matrices in scripts and in dynamically linked code. The octave sparse functions the compared with their equivalent functions with Matlab, and benchmark timings are calculated.
منابع مشابه
. M S / 06 04 00 6 v 1 3 A pr 2 00 6 SPARSE MATRIX IMPLEMENTATION IN OCTAVE
This paper discusses the implementation of the sparse matrix support with Octave. It address the algorithms that have been used, their implementation, including examples of using sparse matrices in scripts and in dynamically linked code. The octave sparse functions the compared with their equivalent functions with Matlab, and benchmark timings are calculated.
متن کاملJoint Classification and Parameter Estimation of Compressive Sampled FSK Signals
This paper deals with the classification and parameter estimation of frequency-shift-keying (FSK) signals that are acquired using a compressive sampling approach. Such a technique allows reducing the sampling frequency needs, as the FSK signals are compressible in the frequency domain; the spectrum of FSK signal is sparse, being concentrated to a finite number of harmonics which depend on the m...
متن کامل2: 3: 4-Harmony within the Tritave
In the Pythagorean tuning system, the fifth is used to generate a scale of 12 notes per octave. In this paper, we use the octave to generate a scale of 19 notes per tritave; one can play this scale on a traditional piano. In this system, the octave becomes a proper interval and the 2:3:4 chord a proper chord. We study harmonic properties obtained from the 2:3:4 chord, in particular composition ...
متن کاملOctave: Past, Present, and Future
This paper outlines the history and development of GNU Octave, an interpreter for a high-level matrix-based language for numerical computations. A number of undesirable features of the current implementation are examined, and proposals for future development are presented.
متن کاملBayesian Modeling with Gaussian Processes using the GPstuff Toolbox
Gaussian processes (GP) are powerful tools for probabilistic modeling purposes. They can be used to define prior distributions over latent functions in hierarchical Bayesian models. The prior over functions is defined implicitly by the mean and covariance function, which determine the smoothness and variability of the function. The inference can then be conducted directly in the function space ...
متن کاملذخیره 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 ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- CoRR
دوره abs/cs/0604006 شماره
صفحات -
تاریخ انتشار 2006