random function signal 中文意思是什麼
random function signal
解釋
隨機函數信號-
The pseudo - random fsk / psk multi - modulation signal and the partly - matched processing signal remain the information of the target of interest. compared with the other processing methods, the partly - matched procession could depict the target ' s information effectively, and could get a higher output snr under a noisy environment. in this dissertation, the deduction and the simulink on the computer of the average ambiguity function of the pseudo - random fsk / psk multi - modulation signal are presented. also, to the partly - matched procession, analysis in theory and simulink on computer are presented. the partly - matched procession applied in radar field is also discussed
較其它處理方法，非完全匹配處理能有效的突出所觀測目標的信息，以及在加噪情況下，其具有高的輸出信噪比。在論文中，對偽隨機fsk / psk復合調制信號的模糊特性進行了推導與模擬，對非完全匹配處理方法進行了理論上的分析以及計算機上的模擬驗證，討論了其在雷達中的應用。 -
Secondllv in the 1 d random traffic flow model. the relation function between the correlation and the creation. disappearance. brake probabilities of the vehicles is presented. according to the statistical mechanical approach to the spatial correlation functions. the theoretical results agree with that of the computer simulation. thirdh. based on the bml model. a main - road traffic flow model with two speeds on two dimensions is designed. this model simulate the traffic situation of one main road and several branches in the cit traffic lights placed on the crossing. vehicles breaking ~ vhile running and turning to other direction while jamming. we investigate the ~ ' e1ocitv and flo ~ ~ of the model when the initial densitvthe brake and turning probabilities. the green to signal rati3. thc number of the branches and the period of the signal are changed. then the reasons causing all the kinds of phenomena are analvzed. finallv. we simulate the bml model using the method of lattice boltzmann which ~ vas brought out by liu mu - renand obtain the velocity - density graph similar to the previous result. the upper critical densiw above which there are oniv jamming configurations. and the lo ~ ver critical density below which there are only moving configurations are the same as before. the boltzmann function which is on the lattices shows the moving and jaxmning transition obviouslv. thus it proves the possibilit of this method on the traffic research
接著，建立了和研究了二維二速的主幹道模型，該模型模擬了城市交通中一條主幹道，多條支道的交通情況，在幹道與支道的交叉路口設置紅綠燈，車輛在運行中可以有對突發事件發生反應的剎車，在發生堵塞時，路口的車輛可考慮通過轉向來緩解交通等各種實際情況的發生，給出了車輛演化的演化方程，並通過計算機模擬，研究模型在改變車輛的初始密度、剎車概率、轉向概率、支道數、紅綠燈信號的綠信比、紅綠燈信號周期等各種情況下支、主幹道車輛的速度、流量的變化，並分析在各種情況下交通狀況的成因，提出改善交通的有效措施。最後，在劉慕仁提出的用格子boltzmann方法研究一維決定論交通流的思路下，將此法推廣到對二維bml模型的模擬上，得到了與用以往方法的研究結果相類似的速度-密度圖線，且車輛從運動相到堵塞相轉變的上下臨界密度是一致的，同時分別給出車輛在處于暢通相和堵塞相時， boltzmann函數在格子上的分佈情況，進一步驗證了此法的可行性。 -
Frequency code is not uniformity distribution and keeps to a probability distribution function defined by the spectral characteristics of the target of interest. the phase code is equally duality pseudo - random sequence and used to reduced the sidelobes of the signal correlation function. and the mismatch - phase sequence is corresponding with the frequency sequence one by one
而頻率編碼為不均勻分佈，由所觀測目標的頻譜信息提取出概率密度函數決定頻率編碼序列的分佈；相位編碼為二元的偽隨機序列，採取均勻的二相編碼，消減同頻脈沖帶來的過高的相關函數的旁瓣；而失配相位為與頻率編碼相一一對應于各子脈沖中。 -
This paper studies a design method of decentralized signal detection system which consists of adaptive fuzzied local - detectors and a data fusion rule of on - line self - learning weights. the local - detectors for inaccurate signal parameters are modeled by means of fuzzy sets which can be adapted to change of the inaccurate signal parameteres. the data fusion center where the optimal declsion rules are used as objective function can learn the local decision weights on - line. the robustness of the fuzzied local - detectors and the adaptability of the self - learned fusion rule make it true that the detection performance of the decentralized detection system is improved under uncertainty and this system can also process the decentralized signal detection with a unknown parameter of unknown distribution or non - random unknown parameter
本文研究了一種由局部自適應模糊檢測器和在線自學習融合演算法所構成的分散式信號檢測系統的設計方法.由模糊集對不精確信號參數的局部檢測器進行建模，該模糊模型可自適應不精確信號參數的變化.融合中心以最佳融合規則作為目標函數在線自學習局部判決的權重.局部模糊檢測器的魯棒性和自學習融合演算法的自適應性使該分散式檢測系統在不確定環境下的檢測性能得到提高.也使該系統能夠處理未知分佈的未知參數以及非隨機未知參數的分散式信號檢測
分享友人