Download “Cross Wavelet and Wavelet Coherence Toolbox”

14 sec read

The “Cross Wavelet and Wavelet Coherence Toolbox” download link by Grinsted et al (http://www.pol.ac.uk/home/research/waveletcoherence/) is dead. We will send you an active download link upon your request (an email with the download link will be sent to you automatically after you fill the form below):





To learn more about wavelet coherence analysis, see https://www.alivelearn.net/?s=wavelet

第十二期 fNIRS Journal Club 视频

在2020/9/26日, 华东师范大学李先春教授和他的学生陈美为大家讲解他们今年发表的一篇用近红外超扫描揭示欺骗行为神经机制的文章。视频如下: Youtube:https://www.youtube.com/watch?v=Qyn1vqUetiQYouku:https://v.youku.com/v_show/id_XNDg3ODkxOTA0MA==.html
Xu Cui
6 sec read

第十三期 fNIRS Journal Club 通知 2020/10/24,10am

北京时间2020年10月24日周六上午10点, 华东师范大学青少年健康评价与运动干预教育部重点实验室、华东师范大学体育与健康学院李琳教授将为大家讲解她们今年发表的一篇用近红外超扫描揭示团体体育运动(篮球)增强合作行为的文章。欢迎大家参加并参与讨论。 时间: 北京时间2020年10月24日周六上午10点地点: https://zoom.com房间号: 865 4354 8112密码: 497127 她要讲解的文献如下: Li, Wang, Luo, Zhang, Zhang, Li (2020) Interpersonal Neural Synchronization During Cooperative Behavior of...
Xu Cui
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第十二期 fNIRS Journal Club 通知 2020/9/26,10am

北京时间2020年9月26日周六上午10点, 华东师范大学李先春教授将为大家讲解他们刚刚发表在 Human brain mapping 的一篇用近红外超扫描揭示欺骗行为的男女差别的文章。欢迎大家参加并参与讨论。 时间: 北京时间2020年9月26日周六上午10点地点: https://zoom.com房间号: 841 2136 8036密码: 603763 他要讲解的文献如下: Chen, Zhang, Zhang, Wang, Yin, Li, Liu, Liu, Li (2020)...
Xu Cui
1 min read

2 Replies to “Download “Cross Wavelet and Wavelet Coherence Toolbox””

  1. Dear Prof. Xu,
    I am writing to get more information about SVM classification.

    I have one matrix with the inputs of the training data (X) and matrix with the labels (e.g. Y, my labels are -1, 1). I would like to do cross validation with n-fold (for example n=10) test on my data and I am going to obtain accuracy, Sensitivity and Specificity parameters to determine the performance of classifier.
    I did my classification based on your tutorial (http://www.alivelearn.net/?s=libsvm).

    bestcv = 0;
    for log2c = -1:3,
    for log2g = -4:1,
    cmd = [‘-v 5 -c ‘, num2str(2^log2c), ‘ -g ‘, num2str(2^log2g)];
    cv = svmtrain(heart_scale_label, heart_scale_inst, cmd);
    if (cv >= bestcv),
    bestcv = cv; bestc = 2^log2c; bestg = 2^log2g;
    end
    fprintf(‘%g %g %g (best c=%g, g=%g, rate=%g)\n’, log2c, log2g, cv, bestc, bestg, bestcv);
    end
    end
    Based on this code I can obtain cross validation accuracy, but in addition to accuracy I would like to obtain “predicted_label” according to cross validation.
    Would you please guide me how can I obtain final predicted_label after cross validation.

    Many thanks for kindly considering my question.
    I look forward to hearing from you.
    Best,
    Iman

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