網路識別信號 的英文怎麼說

中文拼音 [wǎnglùzhìbiéxìnháo]
網路識別信號 英文
network identification signal
  • 網 : Ⅰ名詞1 （捕魚捉鳥的器具） net 2 （像網的東西） thing which looks like a net 3 （像網一樣的組織或...
  • 路 : 1 （道路） road; way; path 2 （路程） journey; distance 3 （途徑; 門路） way; means 4 （條理） se...
  • 識 : 識Ⅰ動詞[書面語] （記） remember; commit to memory Ⅱ名詞1. [書面語] （記號） mark; sign 2. （姓氏） a surname
  • 別 : 別動詞[方言] （改變） change （sb. 's opinion）
  • 號 : 號Ⅰ名1 （名稱） name 2 （別號; 字） assumed name; alternative name3 （商店） business house 4 （...
  • 網路 : 1. [電學] network; electric network2. （網） meshwork; system; graph （指一維復形）; mesh
  • 識別 : 1 （辯別; 辯認） discriminate; distinguish; discern; tell the difference; spot 2 [計算機] identif...
  1. As to the critical technological problems of the interlock control of three - car coke oven - oven number identification, accurate contraposition and data transmission, the author proposes solutions respectively - rfid, three - light positioning device, coke oven controller and radio transmission network. these solutions can ensure accurate identification of the oven number. for example, the deviation of the automatic parking position is within 10mm

    針對三車聯鎖控制環節的關鍵技術：爐號識別、精確對正和數據通信，本系統採用了射頻識別（ rfid ）裝置、三燈位置檢測裝置、焦車控制器、無線通訊網路等解決方案，可實現無差錯的爐號識別，自動停車定位誤差在10mm以下，通信數據可靠等系統要求。
  2. The thesis presents a expert system for identifies power quality disturbance signal, after compare the artificial neural network, nearest neighbors, fuzzy decision, and expert system. we bring forward the project flexible rule - based expert system, according to the characteristic inspection and measure system, and has a deep research on the problem of this system. this project for disturbance classifies has lower mistake ratio and facility maintenance

    採用專家系統的方法進行模式識別，在對神經網路、最近鄰法、模糊邏輯和專家系統及一些交叉方法等模式識別方法進行比較分析的基礎上，根據電能質量信號故障分析的特點，提出了採用規則基專家系統的方法，該模式識別方法具有便於擴展、修改和識別率高等特點。
  3. Furthermore, in order to supplement multi - object tt & c capability of new generation space tt & c system, gmsk modulation is recommended by ccsds because of its preferable frequency speciality and miscode performance. the thesis analyzed characteristic and demodulation realized of gmsk signal. attempting to design a universal multi - mode demodulator of bpsk, qpsk and gmsk, the thesis studied

    本文分析了gmsk信號的特點及解調實現，試圖設計一種bpsk 、 qpsk 、 gmsk通用的多模式解調器，因而研究了調制識別技術，分析了以決策論為基礎的三種信號的調制識別方法，並提出了基於人工神經網路的調制識別方法。
  4. This method can reflect local signal feature and well perform in the experiments. we also present an integrated electromyographic signal ( emg ) pattern recognition scheme. the application of an artificial neural network ( ann ) technique together with a feature extraction technique, for the classification of emg signals is described

    利用高階譜技術提取肌電信號的特徵信息，然後利用奇異值或者其它方法對二維特徵矩陣進行優化，將優化之後的一維特徵向量輸入神經網路分類器進行模式識別，這種方法能夠初步識別不同模式的上肢運動。
  5. The potential applications of amr include both civil and military communication, especially non - cooperative communications and communication confrontation, such as identifying signals, supervising signals, distinguishing interference, electronic confrontation, analyzing military threat, etc. on the basis of our analysis to the existing research on feature abstraction, the related feature abstraction methods are optimized in this paper, resulting several effective methods such as the feature abstraction based on transformation domain, stepped voltage level analysis, normalized carrier - free spectral energy analysis, squared signal and fourth powered signal analysis, etc. both the decision theory based on recognition algorithms and the artificial neural network ( ann ) based on recognition algorithms is analyzed, and the former is selected as it is more appropriate for this research

    調制類型的自動識別廣泛應用於民用通信與軍用通信，尤其是對于非合作性通信、通信對抗，比如：信號確認、信號監控、干擾辨識、電子對抗、軟體無線電、電子救援、通信對抗、軍事威脅分析等。本論文在分析現有研究的基礎上，借鑒了已有的特徵提取方法，對相關調制類型特徵提取方法進行了優化，使用了一些有效的方法，如基於變換域特徵提取方法、梯層電平分析方法、剔除載波后的歸一化頻域能量分析方法、信號平方后的頻譜分析方法、信號四次方后的頻譜分析方法等。通過對基於決策理論和基於人工神經網路兩種識別演算法進行分析，本論文選擇了較適合的基於決策理論的識別演算法。
  6. First, realized a wegener - willie distribute based network traffic anomaly detection algorithm. we make use of wegener - willie distribute to analyze the inherent time - frequency distribution characteristics of the traffic flow signal. then according to the experience of analysis on historical flow, we construct a normal flow training sample aggregation and a abnormal flow training sample aggregation

    通過魏格納-威利分佈分析網路流量信號在時頻分佈上所反映出的內在特點，根據歷史流量的經驗構造正常流量和異常流量兩個訓練樣本空間，通過k最近鄰分類演算法將帶檢測流量信號的時頻分佈與訓練樣本進行比較，完成對檢測樣本的自動分類識別。
  7. Test technique of acoustic excitation presented in this paper can discriminate if the adhesive structure is intensional enough to endure certainty draw strength, through a series of process, for example bringing draw strength to bear on adhesive structure. testing signal through microphone array, choosing signal ' s character, recognizing automatically through manual nerve network, and so on

    本文介紹的粘接構件聲激勵檢測方法，通過對粘結結構施加微力、陣列傳聲器檢測信號、信號的特徵提取、人工神經網路的分類識別等一系列過程，完成了粘接結構承受拉脫力合格與否的無損預報。
  8. Their pd signals are measured and measured cables are anatomized to observe their discharging trace. implement of picking - up character and mode classifying are introduced, and expatiate the principle of artificial neural networks. soft program is necessary to pick - up the character of pd signals and classify pd mode

    論文介紹了由特徵量提取器和模式識別分類器兩大模塊構成的模式識別系統，闡述了人工神經網路的模式識別原理，本文一方面採用信號的prpd模式的放電次數和統計運算元作為bpnn的輸入信號，設計了相應的bpnn模式識別程序；另一方面採用prpd模式的統計運算元作為sart人工神經網路的輸入，設計了相應的sart神經網路模式識別程序。
  9. Improving the recognition rate of eeg in bci based on genetic algorithm and probabilistic neural network

    基於遺傳演算法和概率神經網路提高腦機介面中腦電信號識別率
  10. The integral structure of system are analyzed, and a scheme based on dsps processing board + mcu control board are put forward firstly, following design difficulties and relevant measures. every modules of dsps board are described in details, including chips selection, implementation manners choice, interface and time sequence match and etc. compared otsu single threshold segmentation with multi - threshold segmentations, the latter are preferred to perform the object identification in hardware designed by author. combined to like background rejection, morphology expansion and etc. steps, the paper gets the length of queue ; finally, a - b united control and area united control based on can bus are designed

    首先分析了系統的總體結構，提出了一種基於dsps處理板+單片機控制板的信號機實現方案；在此基礎上，重點介紹了處理板模塊化的硬體電路設計，其中考慮了晶元的選型、實現方式的選擇、工作機制、時序匹配等問題；之後，分析了otsu單閾值目標識別和多閾值目標識別的效果，重點選擇後者在硬體電路板內對圖像進行了目標識別的演算法處理，結合背景的剔除、形態學膨脹等幾個減小誤差的措施，對車輛排隊長度進行了較為精確的提取；最後在控制板上完成了干線a - b信號聯動控制和基於can總線的區域聯網控制的通訊方案設計。
  11. To conquer the problem of acquisition high effectiveness in analog circuit fault imformation, wavelet transform was researched in this paper to preprocess the fault signals. meanwhile, bp neural network diagnosis method based on wavelet transformation was proposed, this method can abstract fault feature effectively and decreases the dimension of imput vector. by this mean, the construct of neural network can be simplified and training time was economized, then the recognize ability of fault type was improved also

    為解決模擬電路的故障信息高效獲取難題，本文採用小波變換作為故障信號的預處理器，研究了基於小波變換預處理的bp網路故障診斷方法，該法能在有效提取故障特徵的同時，降低輸入信息的維數，從而進一步簡化了神經網路的結構，減少了其訓練時間，提高了辨識故障類別的能力。
  12. In the thesis the author presents some research on speaker recognition, mixed speech signal separation and speech transformation using neural network.

    本文介紹作者在進行說話人識別、混疊語音信號分離和應用神經網路技術進行語音轉換方面的若干研究探索問題。
  13. The technology of spectral recognition is key to spectral quapitative analysis. for quickly recognising spectral signal, the method of spectral recognition based on based on multiple features and neural network is adopted. the model transfer is a basic method to solve universal and comparable performance of spectrometers. the method based on support vector machine and piecewise direct standardization is put forward for solve the question of nonlinearity 、 small - sample

    深入探討了光譜信號的識別問題，對光譜識別的基本方法和光譜信號的特徵提取方法進行了相應的分析研究，提出了採用多特徵和神經網路構建光譜識別框架的方法，以實現光譜信號的快速正確地識別。
  14. In this thesis, the fundamental principle and system constituent of the electronic olfactory system are analyzed and studied ; a set of detection system of gas mixture, combined gas sensor array with artificial neural network pattern recognition technology, is designed and constructed. employing this system, the processing ability and identification results of several preprocessing algorithms and artificial neural network models are compared and analyzed. and finally the following conclusions are arrived : 1 ) gas sensor array coupled with pattern recognition technology has the good ability to identify the gas species and quantify its concentration

    本文分析研究了電子嗅覺系統的基本原理和系統組成，設計構建了一套氣體傳感器陣列和人工神經網路模式識別技術相結合的混合氣體檢測系統，並利用這套系統對目前在電子嗅覺系統中使用較廣泛的幾種信號預處理演算法和人工神經網路模型的處理能力和辨識效果進行了分析和比較，最後得出了以下結論： 1 ）氣體傳感器陣列與模式識別技術相結合能夠很好地分析和辨識混合氣體組份及其濃度。
  15. In this paper the measurement of conductive emi emission is discussed, and the design of cm / dm discrimination network is also presented, further, the performance of insertion loss ( il ) and common - mode rejection ( cmr ) is researched, together with the test approach and experiment results

    摘要分析了傳導性電磁干擾信號的測量方法，提出基於共模差模（ cm / dm ）信號的識別網路設計，進一步研究了模態識別網路的插入損耗（ il ）及共模抑制比（ cmr ）等重要性能，並給出模態識別網路的性能實驗設計與分析方法。
  16. In the training this network ' s topology structure and mapping function are the most optimal all along. and the learning velocity and precision are improved. with this recognition method shape pattern information and magnitude can be received rapidly and exactly, which can provide reliable data for later shape controlling

    本文將優化網路用於板形信號的模式識別，建立了6輸入、 3輸出的識別網路模型，該網路性能在訓練過程中始終保持最優，能夠達到最佳結構，加快了學習速度和訓練精度，可以快速、準確求出板形缺陷的模式信息及數值大小，為后續板形控制調節量的設定提供了可靠依據。
  17. This thesis discusses on the post - processing of sonar signal which includes the search and location of the target, the pattern recognition and the neural networks classification, and also carries out a process of the sea test data with the post - process - programs to verify the validity of the pattern recognition with bp neural network, which helps to develop the sonar image processing and the image processing of other fields

    本文在完成課題中的顯示控制任務同時，對聲納信號後置處理，包括目標的搜索定位以及模式識別和神經元網路識別等內容，進行了論述，並利用後置圖像處理程序對正樣機海試數據進行處理，驗證了bp神經元網路下模式識別方法在水聲圖像處理方面的有效性，有助於聲納圖像處理以及其他領域圖像處理的發展。
  18. Operator on prpd mode of pd signal, mode - classifying implements based on bpnn and sart are compiled. the artificial neural networks designed are applied to recognize measured signals. conclusions are made : recognition rate of bpnn is 95 %, and it is respect to magnitude of discharging signal and increases while signal magnitude increasing ; the recognition rate of sart neural network is 98 %, higher than that of bpnn, recognition rate increasing with the number of signal group

    論文用設計的人工網路模式識別程序識別測量信號：以prpd信號模式的放電次數為輸入時， bp網路識別率為88 ，識別率和發生局放的強弱程度有關，局放信號越強，識別率越高；以prpd信號模式的統計運算元為輸入時， bp網路識別率為95 ；以prpd信號模式的統計運算元為輸入時， sart網路識別率為98 ，識別率隨著樣本量的增加而提高。
  19. Classification and identification of communication signal using artificial neural networks

    基於人工神經網路的通信信號分類識別
  20. Rough - set - based fuzzy - neural - network system for taste signal identification

    粗糙集模糊神經網路味覺信號識別系統
分享友人
分享到 Line

分享到臉書