分析for i=E step E until E do i=E
上傳時間： 2013-12-03
上傳用戶：GHF
Implement the step 2 of two-level logic minimization. Our goal is to find the minimum (exact minimum) sum-of-products expression for a given function.
標簽： minimization Implement the two-level
上傳時間： 2014-01-09
上傳用戶：無聊來刷下
This the mathematical computational method of step-vary Gill method.
標簽： method computational mathematical step-vary
上傳時間： 2014-01-02
上傳用戶：lili123
很全的中斷手冊。 INT 00 - CPU-generated - DIVIDE ERROR INT 01 - CPU-generated - SINGLE STEP (80386+) - DEBUGGING EXCEPTIONS INT 02 - external hardware - NON-MASKABLE INTERRUPT INT 03 - CPU-generated - BREAKPOINT INT 04 - CPU-generated - INTO DETECTED OVERFLOW INT 05 - PRINT SCREEN CPU-generated (80186+) - BOUND RANGE EXCEEDED INT 06 - CPU-generated (80286+) - INVALID OPCODE INT 07 - CPU-generated (80286+) - PROCESSOR EXTENSION NOT AVAILABLE INT 08 - IRQ0 - SYSTEM TIMER CPU-generated (80286+) . . .
標簽： CPU-generated INT DIVIDE SINGLE
上傳時間： 2013-12-27
上傳用戶：aa54
How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.
標簽： the decision clusters Cluster
上傳時間： 2013-12-21
上傳用戶：gxmm
porting ucos2 the step way
上傳時間： 2013-12-11
上傳用戶：wl9454
一篇關于XML與STEP模型轉換碩士論文，看后本人受益很多，希望對大家也有幫助
上傳時間： 2013-12-22
上傳用戶：jhksyghr
程控噴泉程序,用step 7 編寫的一個實例。對初學者有幫助。
上傳時間： 2016-03-16
上傳用戶：qb1993225
mirco step 步進電機驅動參考資料
上傳時間： 2014-01-07
上傳用戶：diets
runs Kalman-Bucy filter over observations matrix Z for 1-step prediction onto matrix X (X can = Z) with model order p V = initial covariance of observation sequence noise returns model parameter estimation sequence A, sequence of predicted outcomes y_pred and error matrix Ey (reshaped) for y and Ea for a along with inovation prob P = P(y_t | D_t-1) = evidence
標簽： matrix observations Kalman-Bucy prediction
上傳時間： 2016-04-28
上傳用戶：huannan88
