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feed-forward neural network in Chinese

Pronunciation:
How to pronounce "feed-forward neural network""feed-forward neural network" in a sentence

Translationmobile phoneMobile

  • 反向傳輸神經(jīng)網(wǎng)絡(luò)

Examples

  • Feed - forward neural network based on gaussnewton - nl2sol algorithm and its application
    法的前饋神經(jīng)網(wǎng)絡(luò)及應(yīng)用
  • Chapter 2 focuses on weight learning and structure learning of multi - layer feed - forward neural networks
    主要研究前向神經(jīng)網(wǎng)絡(luò)的權(quán)值學習和結(jié)構(gòu)學習方法。
  • This paper is mainly devoted to the principle and the implemental algorithms of qualitative learning for feed - forward neural networks ( fnns )
    本文主要研究前向神經(jīng)網(wǎng)絡(luò)定性學習的原理和學習算法。
  • Wavelet neural network ( wnn ) is a novel feed - forward neural network based on wavelet theory , and it possesses several excellent features
    摘要小波神經(jīng)網(wǎng)絡(luò)是建立在小波理論基礎(chǔ)上的一種新型前饋神經(jīng)網(wǎng)絡(luò)，具有許多優(yōu)良特性。
  • Based on rbf neural network and perceptron neural network , a four - layer feed - forward neural network named radial basis perceptron ( rbp ) network is presented
    基于rbf網(wǎng)絡(luò)和感知器( perceptron )網(wǎng)絡(luò)建立一四層前饋神經(jīng)網(wǎng)絡(luò)?徑向基感知器( radialbasisperceptron ， rbp )網(wǎng)絡(luò)。
  • The feed - forward neural network is provided to recognizing the currency values , which makes use of the capability to extract features automatically and the error tolerance of neural networks
    利用神經(jīng)網(wǎng)絡(luò)自動特征提取能力和容錯特性，提出使用前饋神經(jīng)網(wǎng)絡(luò)對面值進行識別。
  • Firstly , studied feed - forward neural network and put forward a new algorithm on bp network , called bp algorithm based on robust error function ( bparef ) , and the algorithm is proved to be effective for approaching nonlinear system
    首先研究了前饋神經(jīng)網(wǎng)絡(luò)，提出了基于魯棒誤差函數(shù)的bp神經(jīng)網(wǎng)絡(luò)的算法，并且驗證了其對非線性系統(tǒng)逼近的有效性。
  • In the last of this paper we apply our algorithms to the learning of feed - forward neural network , and get some new learning algorithms . we also give some numerical experiments to compare our algorithms with others
    最后，將得到的這些優(yōu)化加速收斂方法應(yīng)用到了多層前饋神經(jīng)網(wǎng)絡(luò)的學習過程，給出了加速收斂的bp算法，通過實際神經(jīng)網(wǎng)絡(luò)學習問題驗證了工作的成效。
  • Recently a covering method for feed - forward neural network design has been proposed by professor zhang ling . based on the sphere neighborhood model , this method transforms the design of neural classifiers to a geometrical covering problem
    近來張鈴教授提出了一種前饋神經(jīng)網(wǎng)絡(luò)設(shè)計的覆蓋方法，它以球面領(lǐng)域模型為基礎(chǔ)，使得神經(jīng)網(wǎng)絡(luò)的設(shè)計轉(zhuǎn)化為幾何覆蓋問題。
  • To overcome the limitations of general fnns and bp algorithm , this thesis introduced a hybrid feed - forward neural network , which is composed of a linear model and a general multi - layer fnn , and proposed a new learning algorithm for the hybrid fnn
    其次，針對bp網(wǎng)絡(luò)存在的缺陷，結(jié)合前向神經(jīng)網(wǎng)絡(luò)和線性最小二乘法的優(yōu)點，構(gòu)造了一種基于混合結(jié)構(gòu)的神經(jīng)網(wǎng)絡(luò)，提出了相應(yīng)的非迭代的快速學習算法。
  • More examples：  1  2
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