Apriori算法的JAVA實現A priori算法的JAVA實現
上傳時間： 2013-12-23
上傳用戶：13188549192
The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order
標簽： identification considered features separati
上傳時間： 2016-09-20
上傳用戶：FreeSky
The ICA/BSS algorithms are pure mathematical formulas, powerful, but rather mechanical procedures: There is not very much left for the user to do after the machinery has been optimally implemented. The successful and efficient use of the ICALAB strongly depends on a priori knowledge, common sense and appropriate use of the preprocessing and postprocessing tools. In other words, it is preprocessing of data and postprocessing of models where expertise is truly ne
標簽： mathematical algorithms mechanical procedures
上傳時間： 2015-03-31
上傳用戶：silenthink
Versatile visual servoing without knowledge of true jacobian.pdf cobian matrix estimator. The Jacobian matrix estimator does not need a priori knowledge of the kinematic structure and parameters of the robot system, such as camera and link parameters. The proposed visual servoing control scheme ensures the convergence of the image-features to desired trajectories, by using the estimated Jacobian matrix, which is proved by the Lyapunov stability theory. To show the effectiveness of the proposed scheme, simulation and experimental results are presented.
標簽： Versatile knowledge estimator servoing
上傳時間： 2016-08-26
上傳用戶：大三三
This paper presents a Hidden Markov Model (HMM)-based speech enhancement method, aiming at reducing non-stationary noise from speech signals. The system is based on the assumption that the speech and the noise are additive and uncorrelated. Cepstral features are used to extract statistical information from both the speech and the noise. A-priori statistical information is collected from long training sequences into ergodic hidden Markov models. Given the ergodic models for the speech and the noise, a compensated speech-noise model is created by means of parallel model combination, using a log-normal approximation. During the compensation, the mean of every mixture in the speech and noise model is stored. The stored means are then used in the enhancement process to create the most likely speech and noise power spectral distributions using the forward algorithm combined with mixture probability. The distributions are used to generate a Wiener filter for every observation. The paper includes a performance evaluation of the speech enhancer for stationary as well as non-stationary noise environment.
標簽： Telecommunications Processing Signal for
上傳時間： 2020-06-01
上傳用戶：shancjb
