The new method can also be applied to other pattern recognition problems.
该方法也可用于解决其它模式识别问题。
Most of the ideas and algorithms can be applied to other pattern recognition problems.
本文的很多设计思想和算法可以用于许多其他识别问题。
For any kinds of pattern recognition problems, there are some values of application or reference in it.
对于各种模式识别的情况，它都具有一定的实用和参考价值。
After working through the book you will have written code that USES neural networks and deep learning to solve complex pattern recognition problems.
在完成本书的学习后，你将可以编写代码来使用神经网络和深度学习来解决复杂的模式识别问题。
Support vector machine (SVM) is an important learning method of statistical learning theory, and is also a powerful tool for pattern recognition problems.
支持向量机是统计学习理论的一个重要的学习方法，也是解抉模式识别问题的一个有力的工具。
Many practical pattern recognition problems, such as recognition of handwritten Chinese characters belong to the pattern recognition problems of large scale.
许多实际的模式识别问题如对手写体汉字的识别，都属于大规模的模式识别问题。
So, we study the pattern recognition problems from the view of uncertainty reasoning and reveal the nature of various pattern recognition methods, which will be significant.
因此，我们从不确定性推理的角度研究模式识别问题，从而揭示各种模式识别方法的统一的本质，就显得非常有意义。
To solve the pattern recognition problems, the neural network can achieve the involved demarcate of earmark space, and it cut out for high acceleration and parallel systems to achieve.
神经网络对于解决模式识别问题来说，可以实现特征空间较复杂的划分，适合于高速并行处理系统来实现。
Since the data samples in machine learning and pattern recognition problems generally distribute in multi-modal distribution, this thesis proposed a prototype based feature ranking model.
由于模式识别、机器学习等问题的复杂性比较高，数据分布通常呈现多模态分布。
For instance, once we have learned how a specific expert solves his problems, this may be used more generally and thereby becomes a rule in structural pattern recognition.
例如，一旦我们知道一个专家怎么去解决他的问题，于是可以把他的方法更一般化，结果形成结构模式识别中的一条规则。
Neural network can solve some problems of blast furnace expert system such as knowledge getting and inference ability, and it is suitable for pattern recognition of blast furnace data distribution.
神经网络可以解决高炉专家系统最困难的知识获取与推理能力弱等问题，并适合于对高炉分布数据进行模式识别。
Feature extraction is one of the key problems in pattern recognition system.
特征提取是模式识别中的一个关键问题。
Establishing affine invariant similarity measure of shapes is one of the basic problems in pattern recognition, computer vision and image understanding domains.
建立仿射不变的形状相似性度量是模式识别、计算机视觉和图象理解领域中的基本问题之一。
Decision tree learning strategy have long been popular in pattern recognition, machine learning, and other disciplines for solving problems concerned with the classification.
决策树学习策略广泛应用于模式识别和机器学习等领域，用来解决与分类相关的问题。
Based on concepts of attribute measurement, we used attribute clustering network approach to resolve some problems of pattern recognition.
在属性测度概念的基础上，运用属性聚类网络方法解决模式识别问题。
This paper introduces briefly conception of fingerprint chromatography, analytical methods, methods for evaluating the similarity, chemical pattern recognition and problems.
本文概述了近年来中药指纹图谱的构建方法、相似度评价方法、化学模式识别、存在问题。
In fact, the image shift, scale, rotation invariance problems encountered in some pattern recognition tasks can easily be solved in this system.
事实上，某些图像识别任务碰到的图像位移、尺寸、旋转不变性问题，本系统可容易地予以解决。
Finally, the three kinds of models on pattern recognition are summarized in the research of practical problems.
并在具体问题的研究中，总结出三种模式识别模型。
It has obvious advantages in large dimensional or non-deterministic pattern data recognition problems in addition to all merits of WISARD.
它除了保持WISARD的原有特点之外，在解决大维数或非确定性模式数据的识别问题以及控制系统成本方面有着明显的优势。
Representation the high-dimensional data in a low-dimensional subspace is one of the fundamental problems in data analysis, pattern recognition, machine learning, and computer vision.
在低维空间描述高维数据是数据分析、模式识别、机器学习、计算机视觉等领域的基础问题之一。
For these who research into image processing and pattern recognition, the problems under consideration can be seen as reasoning under uncertainty.
对于图像处理和模式识别研究人员来说，所遇到的问题都可以归结为不确定性推理的研究。
Main problems in the research of pattern recognition are discussed in this paper.
本文讨论了模式识别研究中存在的一些主要问题。
Multiple classifiers ensemble is an effective method to solve complex classification problems in pattern recognition field.
多分类器组合是解决复杂模式识别问题的有效办法。
For pattern recognition, the R-transformation will be used. Some special problems with ground target image recognition are considered, too.
在对图象的识别上，采用了基于R变挟的R描绘子来进行分析，并考虑了用于地标识别时的特殊问题。
Support Vector Machine (SVM) is an intellectual learning method based on the statistics theory. The SVM can solve problems of complicated nonlinear pattern recognition of spatial samples.
支持向量机(SVM)是基于统计学习理论的一种智能学习方法，可以用来解决样本空间的高度非线性的模式识别等问题。
It has wide range application areas to apply in pattern recognition due to its powerful information process capability, especially in classification problems.
由于其具备强大的信息处理能力，被广泛应用于模式识别领域，尤其是分类问题。
As one of the most important and typical problems in image processing and computer vision fields, image segmentation is the basic premise in image vision analysis and pattern recognition.
图像分割是图像处理与计算机视觉领域低中最基础和重要的领域之一，是图像进行视觉分析和模式识别的基本前提。
Self organizing feature map (SOM) network can extract the internal features of parameter by self organizing and reflect them on the classified map. It can be used in problems of pattern recognition.
自组织特征映射(SOM)神经网络能通过自组织有效地提取出各特征参数间的内在特征并映射到分类模板上，它可以用于各种模式识别问题。
Face recognition often meet these problems, the dimension of sample too high, the classes of pattern too Mach and each person could only provide a small amount training sample.
人脸识别过程中会遇到各种问题，其中样本维数过高、类别数大、单人训练样本少以及识别的实时性都是亟待解决的难题。
Face recognition often meet these problems, the dimension of sample too high, the classes of pattern too Mach and each person could only provide a small amount training sample.
人脸识别过程中会遇到各种问题，其中样本维数过高、类别数大、单人训练样本少以及识别的实时性都是亟待解决的难题。
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