neural assembly 中文意思是什麼
neural assembly
解釋
神經集合-
The basic thought is to divide the cities which are close to each other into a group ( physical area ) by applying sorting neural network, find out the optimal path by the improved hnn, and then calculate the local optimal path by using the same method, and finally get the whole optimal path, which are described as following : a assembly s of cities is grouped into some subsets according to their physical location and we can get, and then get the optimal, path of tsp of s = { s, i = 1, 2, n } through the given method, as well as the st
基本思想是利用聚類神經網路先把地理位置上相互靠近的城市劃分為一個集體單位（一個物理區域） ，用改進的hopfield神經網路演算法求解各個區域間的最優（或近似最優）路徑，然後再在每一個區域內部用同樣的方法來求解其局部的最優（或近似最優）路徑，這樣可以最終得到全局的最優（或近似最優）解。描述如下：設有城市集合s ，按城市的地理位置把s劃分為若干子摘要2集，得s ijs ， ，其中廠s ； d ， i一口求得集合i叫s s ； i習， 2 ， … n的tsp最優路徑，再依次求得子集s ；內部的tsp最優路徑，即得最終優化路徑m一） s一） …一寧s ； di -
Based on the historical space forecast data and corresponding actual data provided by a global semiconductor assembly and test company, the uncertainty of space planning was defined. during this analysis process, linear regression, grey prediction, neural network back propagation algorithm and confidence interval were applied, respectively, to define the uncertainty. compared with those methods, the confidence interval of historical space forecast error, calculated by mathematical statistics, was the reasonable method to define the space forecasting uncertainty
本文從半導體工廠長期生產能力計劃的頂層即廠房生產面積的計劃展開，對一跨國半導體封裝測試公司提供的廠房生產面積的長期歷史預測數據以及對應的真實數據進行分析，採用線性回歸，灰預測，神經網路bp演算法，基於數理統計的置信區間的求解等方法分別定義廠房生產面積預測的不確定度，經多種方法的比較得出，基於數理統計方法求解出的生產面積歷史預測誤差置信區間能直觀清楚地標定不確定度。 -
Three algorithms for pseudo - random fsk / psk radar signals ’ sidelobe suppression such as spectrum modifying, direct mismatch filters and neural network. 3. using adsp 21160 to design dsp programs with assembly and c languages for the three algorithms mentioned above on visualdsp + + 3. 5 integrated development environment
3 .用adi公司的sharc系列晶元adsp21160 ，在visualdsp + + 3 . 5集成開發軟體平臺上，完成以上三種旁瓣壓縮演算法實現的匯編、 c語言程序設計和調試工作。
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