neural coding 中文意思是什麼
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Spatiotemporal coding in fitzhugh - nagumo neural network with time delay
神經網路的時空編碼 -
A new stereo image coding algorithm based upon self - organizeing neural network
一種改進的立體圖像編碼演算法 -
In the paper, chapter 1 gives a comprehensive introduction of digital image compressing including its recent status, technical standards, classification in the world. chapter 2 introduces briefly the thought and ii procedure of vector quantization, describes lgb algorithm and vector quantization based on sofm neural network. chapter 3 discusses predictable coding in lossy and lossless aspects, analyzes adaptive predictable coding based on bp neural network, introduces the evaluation of algorithm on neural network in image compression. chapter 4 discusses the applications of mathematical transformation in image compression and does experiments related, analyzes the strategies of image coding in transformed domain. in chapter 5 images are decomposed and represented by wavelet transform, then discusses the characteristics and effects of wavelet functions in image compression, analyzes the wavelet coefficients after images are decomposed ; based on the theories and analyses in the prior chapters, the paper presents an image compression scheme and gives results. the test results shows that the image compression scheme is practical and helpful to map into the local content of images to get rid off redundancy, so that, it can require satisfactory results of image compression
方案首先利用小波多分辨分析性質，對圖像進行小波分解，對分解后各子圖的小波系數進行了統計分析，針對各子圖的小波系數特點，對不同的子圖分別採用不同的壓縮方法，低頻子圖採用基於神經網路的自適應預測編碼，高頻子圖採用基於神經網路的矢量量化編碼，從而實現對圖像數據的壓縮處理。本論文第一章介紹了數字圖像壓縮處理的國內外當前的概況以及其技術標準和分類。在第二章，介紹了數字圖像的矢量量化技術的數學思想和過程，對lbg演算法和基於sofm神經網路的矢量量化進行了闡述、分析。 -
Neural networks are used more frequently in lossy data coding than in general lossless data coding, because standard neural networks must be trained off - line and they are too slow to be practical. in this thesis, statistical language model based on maximum entropy and neural networks are discussed particularly. then, an arithmetic coding algorithm based on maximum entropy and neural networks are proposed in this thesis
傳統的人工神經網路數據編碼演算法需要離線訓練且編碼速度慢，因此通常多用於專用有損編碼領域如聲音、圖像編碼等，在無損數據編碼領域應用較少，針對這種現狀，本文詳細地研究了最大熵統計語言模型和神經網路演算法各自的特點，在此基礎上提出了一種基於神經網路和最大熵原理的算術編碼方法，這是一種自適應的可在線學習的演算法，並具有精簡的網路結構。 -
Reinforcement learning algorithms that use cerebellar model articulation controller ( cmac ) are studied to estimate the optimal value function of markov decision processes ( mdps ) with continuous states and discrete actions. the state discretization for mdps using sarsa - learning algorithms based on cmac networks and direct gradient rules is analyzed. two new coding methods for cmac neural networks are proposed so that the learning efficiency of cmac - based direct gradient learning algorithms can be improved
在求解離散行為空間markov決策過程（ mdp ）最優策略的增強學習演算法研究方面，研究了小腦模型關節控制器（ cmac ）在mdp行為值函數逼近中的應用，分析了基於cmac的直接梯度演算法對mdp狀態空間離散化的特點，研究了兩種改進的cmac編碼結構，即：非鄰接重疊編碼和變尺度編碼，以提高直接梯度學習演算法的收斂速度和泛化性能。 -
Then get " m " groups of figures. use real - number coding and take the neural network weight factor as the chromosome of ga
本文把隨機抽取的m組權值分配到m個神經網路中。 -
In the constructing of the diagnosis module using the technology of the combination of the fuzzy logic and neural network, which based on the fuzzy adaptive learning control network, a simple kind of capable method for consummate the structure and performance of network is introduced, which includes the rules extraction based on the maximum weights matrix and the parameters amendment based on genetic algorithm by floating - point coding. during the monitoring of the parts condition, the output of the condition monitoring system shows the good working condition of the executing agency by fuzzily deducing from the control instruction send by the auv ' s controller and motion status, and so offers the proof to complete mission and return safely
在珍斷模塊建模中採用模糊邏輯與神經網路結合的技術，以模糊自適應學習控制網路為核心，提出了一種簡單可行的基於最大權值矩陣的規則提取及基於浮點數編碼的遺傳演算法的參數調整的，完善網路結構與性能的方法，並在狀態監測過程中，通過對由控制器輸入的水下機器人運動控制量以及運行狀態的模糊推理，得到執行部件（推進器或舵）的工作狀態優劣程度，為保證水下機器人完成任務，安全返回提供控制依據。 -
According to the standard of kddcup ' 99 and by adopting numeric mixed coding, 41 features of the captured network packets are extracted and transferred into numerical form which can be accepted by neural network in this paper, we present a misuse detection model based on hybrid neural network and decision tree
根據第三屆國際知識發現和數據挖掘競賽（ kddcup ' 99 ）標準，對截獲的網路數據包進行41維特徵抽取，並採用混合數值編碼方法，使這些特徵轉化為能被神經網路處理的數值形式。 -
Neural network, which is used widely in many research fields, can do self - adapting and self - learning, so they become a preferable approach for data coding
而在許多領域應用廣泛的人工神經網路具有自適應和自學習的特點，成為數據編碼方法的一個理想選擇。 -
Examples of neural coding. simple linear regression
神經編碼的例子與簡單的線性?歸。 -
In the development of neural network ? s architectures, a sparse coding is put forward
在結構設計中，提出了稀疏化的編碼方法。 -
A kind of multilayer forward neural network based on improved genetic algorithm is applied to build the inverse kinematics model of manipulator, aim at the model, each operator and coding plan of the improved algorithm are discussed in detail, because the first joint of the robot is not rotational, for to unify to the fitness function, the relation model between every joint of the robot and corresponding electromotor rotational angle which is regarded as output sample neural network is build
為此，我們提出應用基於改進的遺傳演算法的神經網路來建立機器人運動學逆問題模型，針對該模型，詳細討論了改進后的遺傳演算法的各個運算元以及編碼方案，並針對該機器人第一關節是平動關節，建立了該機器人各關節與相應驅動電機轉角之間的關系模型，將各關節驅動電機的轉角做為神經網路訓練樣本對的輸出樣本，為統一到適應度函數的公式中做了必要的準備。 -
The genetic algorithm coding in the real number is engaged to optimize the structure and original parameters of bp neural network, so the network can learn the training patterns more accurately
該方法採用實數編碼的遺傳演算法優化bp網路的結構及初始參數，從而提高了網路的精度。 -
The result above indicates that orientation discrimination practising can leads to specific shift of orientation sensitivity for at least part of the dlgn neurons, which may contribute to the neural plasticity of orientation coding in visual cortex
以上結果提示，方位識別訓練可特異性改變外膝體部分神經元（特定離心度上）的方位敏感性，這種敏感性改變可能對視皮層細胞的方位編碼可塑性有貢獻。 -
( 1 ) the paper has studied the contractive mapping genetic algorithm, which can be converged to a global optimal solution proved by fixed - point theorem of banach space. it remedies the shortage of standard genetic algorithm. furthermore, the paper discusses the genetic operation in the algorithm such as the coding, select, cross over and mutation etc. it will be help to the next work about fusion with the neural network
本文融合神經網路技術和遺傳演算法，對軌道交通引起的地面振動進行了正分析和反演，並利用計算機技術實現了地面振動的三維動畫模擬，這主要包括： （ 1 ）研究了壓縮映射遺傳演算法，利用banach空間的不動點定理證明了壓縮映射遺傳演算法可以收斂到全局最優值，彌補了標準遺傳演算法不能收斂至全局最優值的不足。
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