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src/main/java/org/dromara/easyai/nerveEntity/HiddenNerve.java

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+package org.dromara.easyai.nerveEntity;
+
+import org.dromara.easyai.entity.ThreeChannelMatrix;
+import org.dromara.easyai.i.CustomEncoding;
+import org.dromara.easyai.matrixTools.Matrix;
+import org.dromara.easyai.matrixTools.MatrixList;
+import org.dromara.easyai.matrixTools.MatrixOperation;
+import org.dromara.easyai.i.ActiveFunction;
+import org.dromara.easyai.i.OutBack;
+
+import java.util.ArrayList;
+import java.util.List;
+import java.util.Map;
+
+/**
+ * @author lidapeng
+ * 隐层神经元
+ * @date  9:30 上午 2019/12/21
+ */
+public class HiddenNerve extends Nerve {
+    private final boolean isConvFinish;//卷积最后一层
+    private final MatrixOperation matrixOperation = new MatrixOperation();
+
+    public HiddenNerve(int id, int depth, int upNub, int downNub, float studyPoint,
+                       boolean init, ActiveFunction activeFunction, boolean isDynamic, int rzType, float lParam
+            , int kernLen, int matrixX, int matrixY, boolean isConvFinish, int coreNumber, int channelNo, float oneConvStudy, boolean norm
+            , CustomEncoding customEncoding, float gaMa, float gMaxTh, boolean auTo, float GRate) throws Exception {//隐层神经元
+        super(id, upNub, "HiddenNerve", downNub, studyPoint,
+                init, activeFunction, isDynamic, rzType, lParam, kernLen, depth, matrixX, matrixY
+                , coreNumber, channelNo, oneConvStudy, norm, customEncoding, gaMa, gMaxTh, auTo, GRate);
+        this.isConvFinish = isConvFinish;
+    }
+
+    @Override
+    public void input(long eventId, float parameter, boolean isKernelStudy, Map<Integer, Float> E
+            , OutBack outBack) throws Exception {//接收上一层的输入
+        boolean allReady = insertParameter(eventId, parameter);
+        if (allReady) {//参数齐了，开始计算 sigma - threshold
+            float sigma = calculation(eventId);
+            float out = activeFunction.function(sigma);//激活函数输出数值
+            if (isKernelStudy) {
+                outNub = out;
+            } else {
+                destoryParameter(eventId);
+            }
+            sendMessage(eventId, out, isKernelStudy, E, outBack);
+        }
+    }
+
+    @Override
+    protected void inputMatrixFeature(long eventId, List<Float> parameters, boolean isStudy, Map<Integer, Float> E, OutBack imageBack) throws Exception {
+        insertParameters(eventId, parameters);
+        float sigma = calculation(eventId);
+        float out = activeFunction.function(sigma);//激活函数输出数值
+        if (isStudy) {
+            outNub = out;
+        } else {
+            destoryParameter(eventId);
+        }
+        sendMessage(eventId, out, isStudy, E, imageBack);
+    }
+
+    @Override
+    protected void inputMatrix(long eventId, List<Matrix> matrix, boolean isStudy
+            , Map<Integer, Float> E, OutBack outBack, boolean needMatrix) throws Exception {
+        List<Matrix> myMatrix = conv(matrix);//处理过的矩阵
+        if (isConvFinish) {
+            Matrix ourMatrix;
+            if (myMatrix.size() == 1) {
+                ourMatrix = myMatrix.get(0);
+            } else {
+                MatrixList matrixList = new MatrixList(myMatrix.get(0), true, 100);
+                for (int i = 1; i < myMatrix.size(); i++) {
+                    matrixList.add(myMatrix.get(i));
+                }
+                ourMatrix = matrixList.getMatrix();
+            }
+            if (!isStudy && needMatrix) {
+                outBack.getBackMatrix(ourMatrix, getId(), eventId);
+            }
+            sendMatrixList(eventId, matrixOperation.matrixToList(ourMatrix), isStudy, E, outBack);
+        } else {
+            sendMatrix(eventId, myMatrix, isStudy, E, outBack, needMatrix);
+        }
+    }
+
+    @Override
+    protected void inputThreeChannelMatrix(long eventId, ThreeChannelMatrix picture, boolean isKernelStudy, Map<Integer, Float> E, OutBack outBack, boolean needMatrix) throws Exception {
+        //接收三通道矩阵
+        List<Matrix> matrixList = new ArrayList<>();
+        matrixList.add(picture.getMatrixR());
+        matrixList.add(picture.getMatrixG());
+        matrixList.add(picture.getMatrixB());
+        demRedByMatrixList(eventId, matrixList, isKernelStudy, E, outBack, needMatrix);
+    }
+}