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bit parity
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  “bit parity”译为未确定词的双语例句
     The MPT-1327 signaling is an international standard for mobile communication and its methd of error correction is BCH(63,48)plus 1 bit parity. By calculation and simulation,this paper analyzes the performance of the code and introduces a method of error correction with micro-chip computer.
     MPT-1327信令是一种公开的国际性标准,其纠检错采用BCH(63,48)加一位奇偶校验编码格式,文章通过计算和模拟的方法,分析了这种编码的性能,介绍了一种实现纠检错的方式。
短句来源
     The experimental results show that MPENN can solve the XOR problem, the 3 bit parity problem and the sensory quality assessment of cigarettes successfully.
     实验结果表明 ,MPENNs能成功解决异或问题、三元奇偶问题及成品烟的感官质量评价问题。
短句来源
     This class of LDPC codes concatenates multiple single bit parity check block codes in serial, and it makes encoding complexity much lower than in usual ways.
     该类LDPC码综合了LD PC码和级联码的特点,不仅编码算法简单,而且有了固定的码结构。
短句来源
     For optimization design of combinatorial logic circuit of programmable logic device,the design method of circuit is presented based on double-optimization index according to basic characteristic of small-world model clustering of complex network. Using 16 bit parity circuit as an example which is simulated using Matlab.
     针对可编程逻辑器件中组合逻辑电路的优化设计问题,依据复杂网络理论中小世界模型分簇的基本特征,提出了双重优化设计指标下的电路设计方法,以16位奇偶校验电路为例,利用Matlab对电路进行了仿真。
短句来源
  相似匹配句对
     FACTORS AND PARITY
     因子与奇偶性
短句来源
     Bit information of the watermark is embedded by judging and adjusting the parity of pixels.
     选取一些像素点,通过判断并调整这些像素点的灰度值奇偶性达到嵌入水印图像位信息的目的。
短句来源
     Meanwhile,the algorithms of 16QAM Softdemapping parity bit decoding and symbol mapping were derived.
     同时推导了16QAM软去映射、校验比特译码和符号重构算法的数学过程。
短句来源
     Radar BIT design
     雷达机内测试(BIT)的设计
短句来源
     Applications of BIT in DFCS
     BIT技术在数字飞行控制系统中的应用
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  bit parity
The current-mode operation of the analog core combined with differential neuron inputs reaches an analog precision sufficient for 10 bit parity while running at a speed of 0.8 Teraconnections per second.
      
In this paper, we confirm our previous results in further detail and investigate what contributes to the efficiency of our model through 4-bit and 6-bit parity check problems, which are known as basic benchmark tests.
      
Therefore, the πt-neuron solution to the N-bit parity problem has the lowest computational cost among the neural solutions presented to date.
      
A solution to the N-bit parity problem employing a single multiplicative neuron model, called translated multiplicative neuron (πt-neuron), is proposed.
      
A Solution for the N-bit Parity Problem Using a Single Translated Multiplicative Neuron
      
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ANNs for pattern recognition with multi-valued(MV) and multi-thresholded(MT) transfer function as neurons' nonlinearities have been proposed. The function of multithresholded neurons (MTNs) lay in the fact that it partitioned the input space into several hyperplanar zones by using many thresholds in neurons' output transfer function, it also marked these different zones with different output values as required. On the basis of these neurons, the advantage of solving parity problem and specific logic problem...

ANNs for pattern recognition with multi-valued(MV) and multi-thresholded(MT) transfer function as neurons' nonlinearities have been proposed. The function of multithresholded neurons (MTNs) lay in the fact that it partitioned the input space into several hyperplanar zones by using many thresholds in neurons' output transfer function, it also marked these different zones with different output values as required. On the basis of these neurons, the advantage of solving parity problem and specific logic problem was investigated. It had been shown that only one neuron was needed to solve N-bit parity problem or to perform arbitrary logic function.Therefore, it was especially suitable for pattern recognition and classification. The combination of MTNs was also investigated. It was found that two MTNs may result in the multiplication of threshold number of combined net.

本文提出了输出特性具有多值和多阈值特性的神经元。这种新神经元的功能在于它用多个阈值把输入空间划分成多个超平带,并可把各个超平带按需求归类或赋以不同的输出值作为标号。以这类神经元为基础讨论了在解决奇偶校验问题和实现特定逻辑功能方面的优越性。理论上只需一个神经元就能实现任意位的奇偶校验或任意的逻辑功能,因而特别适合在模式识别和分类中应用。论文还研究了多阈值神经元的组合问题,发现二个多阈值神经元的特定组合可以发生阈值数量的倍增现象,这为复杂多阈值神经元的模拟计算与硬件实现提供了方便途径。

The MPT-1327 signaling is an international standard for mobile communication and its methd of error correction is BCH(63,48)plus 1 bit parity. By calculation and simulation,this paper analyzes the performance of the code and introduces a method of error correction with micro-chip computer.

MPT-1327信令是一种公开的国际性标准,其纠检错采用BCH(63,48)加一位奇偶校验编码格式,文章通过计算和模拟的方法,分析了这种编码的性能,介绍了一种实现纠检错的方式。

A novel multigroup parallel genetic algorithm (NMPGA) is presented as a learning method for multilayer feedforward neural networks (MFNN). Consequently, a new MFNN model multigroup parallel evolutionary neural network (MPENN) is formed. First, for a given network, architecture initial weight sets are generated randomly, which in fact are corresponding to a group of MFNN with the same architecture but different weights. Then the NMPGA is adopted to evolve the weights and biases of all the MFNN. In the end the...

A novel multigroup parallel genetic algorithm (NMPGA) is presented as a learning method for multilayer feedforward neural networks (MFNN). Consequently, a new MFNN model multigroup parallel evolutionary neural network (MPENN) is formed. First, for a given network, architecture initial weight sets are generated randomly, which in fact are corresponding to a group of MFNN with the same architecture but different weights. Then the NMPGA is adopted to evolve the weights and biases of all the MFNN. In the end the best network is chosen as a solution to the object problem. In addition, float encoding is introduced to solve the accuracy insufficiency problem of the traditional binary encoding. Furthermore a new crossover operator and a new mutation operator are devised to enhance the algorithm performance. The experimental results show that MPENN can solve the XOR problem, the 3 bit parity problem and the sensory quality assessment of cigarettes successfully.

提出一种新的多种群并行遗传算法 (NMPGA) ,并将其作为多层前馈神经网络(MFNNs)的学习算法 ,从而形成一类新的 MFNN模型——多种群并行进化神经网络(MPENNs)。首先 ,对一给定的网络结构 ,随机产生一初始权重的集合 ,这个集合实际上对应着一组具有相同结构但不同权重的神经网络。然后 ,采用 NMPGA对 MFNNs的权重进行进化。最后 ,性能最好的网络被选作目标问题的解。在 NMPGA算法中 ,作者采用浮点数编码来克服传统二进制编码的精度不足问题 ,并设计了专门的杂交算子和变异算子来增强算法性能。实验结果表明 ,MPENNs能成功解决异或问题、三元奇偶问题及成品烟的感官质量评价问题。

 
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