diff --git a/src/main/java/org/encog/neural/networks/PersistBasicNetwork.java b/src/main/java/org/encog/neural/networks/PersistBasicNetwork.java
index 35b9e3384..4082a6d7b 100644
--- a/src/main/java/org/encog/neural/networks/PersistBasicNetwork.java
+++ b/src/main/java/org/encog/neural/networks/PersistBasicNetwork.java
@@ -1,203 +1,203 @@
-/*
- * Encog(tm) Core v3.1 - Java Version
- * http://www.heatonresearch.com/encog/
- * http://code.google.com/p/encog-java/
- 
- * Copyright 2008-2012 Heaton Research, Inc.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *     http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- *   
- * For more information on Heaton Research copyrights, licenses 
- * and trademarks visit:
- * http://www.heatonresearch.com/copyright
- */
-package org.encog.neural.networks;
-
-import java.io.InputStream;
-import java.io.OutputStream;
-import java.util.List;
-import java.util.Map;
-
-import org.encog.engine.network.activation.ActivationFunction;
-import org.encog.neural.flat.FlatNetwork;
-import org.encog.persist.EncogFileSection;
-import org.encog.persist.EncogPersistor;
-import org.encog.persist.EncogReadHelper;
-import org.encog.persist.EncogWriteHelper;
-import org.encog.persist.PersistConst;
-import org.encog.persist.PersistError;
-import org.encog.util.csv.CSVFormat;
-
-/**
- * Persist a basic network.
- *
- */
-public class PersistBasicNetwork implements EncogPersistor {
-
-	/**
-	 * {@inheritDoc}
-	 */
-	@Override
-	public int getFileVersion() {
-		return 1;
-	}
-
-	/**
-	 * {@inheritDoc}
-	 */
-	@Override
-	public String getPersistClassString() {
-		return "BasicNetwork";
-	}
-
-	/**
-	 * {@inheritDoc}
-	 */
-	@Override
-	public Object read(final InputStream is) {
-		final BasicNetwork result = new BasicNetwork();
-		final FlatNetwork flat = new FlatNetwork();
-		final EncogReadHelper in = new EncogReadHelper(is);
-		EncogFileSection section;
-
-		while ((section = in.readNextSection()) != null) {
-			if (section.getSectionName().equals("BASIC")
-					&& section.getSubSectionName().equals("PARAMS")) {
-				final Map<String, String> params = section.parseParams();
-				result.getProperties().putAll(params);
-			}
-			if (section.getSectionName().equals("BASIC")
-					&& section.getSubSectionName().equals("NETWORK")) {
-				final Map<String, String> params = section.parseParams();
-
-				flat.setBeginTraining(EncogFileSection.parseInt(params,
-						BasicNetwork.TAG_BEGIN_TRAINING));
-				flat.setConnectionLimit(EncogFileSection.parseDouble(params,
-						BasicNetwork.TAG_CONNECTION_LIMIT));
-				flat.setContextTargetOffset(EncogFileSection.parseIntArray(
-						params, BasicNetwork.TAG_CONTEXT_TARGET_OFFSET));
-				flat.setContextTargetSize(EncogFileSection.parseIntArray(
-						params, BasicNetwork.TAG_CONTEXT_TARGET_SIZE));
-				flat.setEndTraining(EncogFileSection.parseInt(params,
-						BasicNetwork.TAG_END_TRAINING));
-				flat.setHasContext(EncogFileSection.parseBoolean(params,
-						BasicNetwork.TAG_HAS_CONTEXT));
-				flat.setInputCount(EncogFileSection.parseInt(params,
-						PersistConst.INPUT_COUNT));
-				flat.setLayerCounts(EncogFileSection.parseIntArray(params,
-						BasicNetwork.TAG_LAYER_COUNTS));
-				flat.setLayerFeedCounts(EncogFileSection.parseIntArray(params,
-						BasicNetwork.TAG_LAYER_FEED_COUNTS));
-				flat.setLayerContextCount(EncogFileSection.parseIntArray(
-						params, BasicNetwork.TAG_LAYER_CONTEXT_COUNT));
-				flat.setLayerIndex(EncogFileSection.parseIntArray(params,
-						BasicNetwork.TAG_LAYER_INDEX));
-				flat.setLayerOutput(section.parseDoubleArray(params,
-						PersistConst.OUTPUT));
-				flat.setLayerSums(new double[flat.getLayerOutput().length]);
-				flat.setOutputCount(EncogFileSection.parseInt(params,
-						PersistConst.OUTPUT_COUNT));
-				flat.setWeightIndex(EncogFileSection.parseIntArray(params,
-						BasicNetwork.TAG_WEIGHT_INDEX));
-				flat.setWeights(section.parseDoubleArray(params,
-						PersistConst.WEIGHTS));
-				flat.setBiasActivation(section.parseDoubleArray(
-						params, BasicNetwork.TAG_BIAS_ACTIVATION));
-			} else if (section.getSectionName().equals("BASIC")
-					&& section.getSubSectionName().equals("ACTIVATION")) {
-				int index = 0;
-
-				flat.setActivationFunctions(new ActivationFunction[flat
-						.getLayerCounts().length]);
-
-				for (final String line : section.getLines()) {
-					ActivationFunction af = null;
-					final List<String> cols = EncogFileSection
-							.splitColumns(line);
-					final String name = "org.encog.engine.network.activation."
-							+ cols.get(0);
-					try {
-						final Class<?> clazz = Class.forName(name);
-						af = (ActivationFunction) clazz.newInstance();
-					} catch (final ClassNotFoundException e) {
-						throw new PersistError(e);
-					} catch (final InstantiationException e) {
-						throw new PersistError(e);
-					} catch (final IllegalAccessException e) {
-						throw new PersistError(e);
-					}
-
-					for (int i = 0; i < af.getParamNames().length; i++) {
-						af.setParam(i,
-								CSVFormat.EG_FORMAT.parse(cols.get(i + 1)));
-					}
-
-					flat.getActivationFunctions()[index++] = af;
-				}
-			}
-		}
-
-		result.getStructure().setFlat(flat);
-
-		return result;
-	}
-
-	/**
-	 * {@inheritDoc}
-	 */
-	@Override
-	public void save(final OutputStream os, final Object obj) {
-		final EncogWriteHelper out = new EncogWriteHelper(os);
-		final BasicNetwork net = (BasicNetwork) obj;
-		final FlatNetwork flat = net.getStructure().getFlat();
-		out.addSection("BASIC");
-		out.addSubSection("PARAMS");
-		out.addProperties(net.getProperties());
-		out.addSubSection("NETWORK");
-
-		out.writeProperty(BasicNetwork.TAG_BEGIN_TRAINING,
-				flat.getBeginTraining());
-		out.writeProperty(BasicNetwork.TAG_CONNECTION_LIMIT,
-				flat.getConnectionLimit());
-		out.writeProperty(BasicNetwork.TAG_CONTEXT_TARGET_OFFSET,
-				flat.getContextTargetOffset());
-		out.writeProperty(BasicNetwork.TAG_CONTEXT_TARGET_SIZE,
-				flat.getContextTargetSize());
-		out.writeProperty(BasicNetwork.TAG_END_TRAINING, flat.getEndTraining());
-		out.writeProperty(BasicNetwork.TAG_HAS_CONTEXT, flat.getHasContext());
-		out.writeProperty(PersistConst.INPUT_COUNT, flat.getInputCount());
-		out.writeProperty(BasicNetwork.TAG_LAYER_COUNTS, flat.getLayerCounts());
-		out.writeProperty(BasicNetwork.TAG_LAYER_FEED_COUNTS,
-				flat.getLayerFeedCounts());
-		out.writeProperty(BasicNetwork.TAG_LAYER_CONTEXT_COUNT,
-				flat.getLayerContextCount());
-		out.writeProperty(BasicNetwork.TAG_LAYER_INDEX, flat.getLayerIndex());
-		out.writeProperty(PersistConst.OUTPUT, flat.getLayerOutput());
-		out.writeProperty(PersistConst.OUTPUT_COUNT, flat.getOutputCount());
-		out.writeProperty(BasicNetwork.TAG_WEIGHT_INDEX, flat.getWeightIndex());
-		out.writeProperty(PersistConst.WEIGHTS, flat.getWeights());
-		out.writeProperty(BasicNetwork.TAG_BIAS_ACTIVATION,
-				flat.getBiasActivation());
-		out.addSubSection("ACTIVATION");
-		for (final ActivationFunction af : flat.getActivationFunctions()) {
-			out.addColumn(af.getClass().getSimpleName());
-			for (int i = 0; i < af.getParams().length; i++) {
-				out.addColumn(af.getParams()[i]);
-			}
-			out.writeLine();
-		}
-
-		out.flush();
-	}
-
-}
+/*
+ * Encog(tm) Core v3.1 - Java Version
+ * http://www.heatonresearch.com/encog/
+ * http://code.google.com/p/encog-java/
+ 
+ * Copyright 2008-2012 Heaton Research, Inc.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *   
+ * For more information on Heaton Research copyrights, licenses 
+ * and trademarks visit:
+ * http://www.heatonresearch.com/copyright
+ */
+package org.encog.neural.networks;
+
+import java.io.InputStream;
+import java.io.OutputStream;
+import java.util.List;
+import java.util.Map;
+
+import org.encog.engine.network.activation.ActivationFunction;
+import org.encog.neural.flat.FlatNetwork;
+import org.encog.persist.EncogFileSection;
+import org.encog.persist.EncogPersistor;
+import org.encog.persist.EncogReadHelper;
+import org.encog.persist.EncogWriteHelper;
+import org.encog.persist.PersistConst;
+import org.encog.persist.PersistError;
+import org.encog.util.csv.CSVFormat;
+
+/**
+ * Persist a basic network.
+ *
+ */
+public class PersistBasicNetwork implements EncogPersistor {
+
+	/**
+	 * {@inheritDoc}
+	 */
+	@Override
+	public int getFileVersion() {
+		return 1;
+	}
+
+	/**
+	 * {@inheritDoc}
+	 */
+	@Override
+	public String getPersistClassString() {
+		return "BasicNetwork";
+	}
+
+	/**
+	 * {@inheritDoc}
+	 */
+	@Override
+	public Object read(final InputStream is) {
+		final BasicNetwork result = new BasicNetwork();
+		final FlatNetwork flat = new FlatNetwork();
+		final EncogReadHelper in = new EncogReadHelper(is);
+		EncogFileSection section;
+
+		while ((section = in.readNextSection()) != null) {
+			if (section.getSectionName().equals("BASIC")
+					&& section.getSubSectionName().equals("PARAMS")) {
+				final Map<String, String> params = section.parseParams();
+				result.getProperties().putAll(params);
+			}
+			if (section.getSectionName().equals("BASIC")
+					&& section.getSubSectionName().equals("NETWORK")) {
+				final Map<String, String> params = section.parseParams();
+
+				flat.setBeginTraining(EncogFileSection.parseInt(params,
+						BasicNetwork.TAG_BEGIN_TRAINING));
+				flat.setConnectionLimit(EncogFileSection.parseDouble(params,
+						BasicNetwork.TAG_CONNECTION_LIMIT));
+				flat.setContextTargetOffset(EncogFileSection.parseIntArray(
+						params, BasicNetwork.TAG_CONTEXT_TARGET_OFFSET));
+				flat.setContextTargetSize(EncogFileSection.parseIntArray(
+						params, BasicNetwork.TAG_CONTEXT_TARGET_SIZE));
+				flat.setEndTraining(EncogFileSection.parseInt(params,
+						BasicNetwork.TAG_END_TRAINING));
+				flat.setHasContext(EncogFileSection.parseBoolean(params,
+						BasicNetwork.TAG_HAS_CONTEXT));
+				flat.setInputCount(EncogFileSection.parseInt(params,
+						PersistConst.INPUT_COUNT));
+				flat.setLayerCounts(EncogFileSection.parseIntArray(params,
+						BasicNetwork.TAG_LAYER_COUNTS));
+				flat.setLayerFeedCounts(EncogFileSection.parseIntArray(params,
+						BasicNetwork.TAG_LAYER_FEED_COUNTS));
+				flat.setLayerContextCount(EncogFileSection.parseIntArray(
+						params, BasicNetwork.TAG_LAYER_CONTEXT_COUNT));
+				flat.setLayerIndex(EncogFileSection.parseIntArray(params,
+						BasicNetwork.TAG_LAYER_INDEX));
+				flat.setLayerOutput(section.parseDoubleArray(params,
+						PersistConst.OUTPUT));
+				flat.setLayerSums(new double[flat.getLayerOutput().length]);
+				flat.setOutputCount(EncogFileSection.parseInt(params,
+						PersistConst.OUTPUT_COUNT));
+				flat.setWeightIndex(EncogFileSection.parseIntArray(params,
+						BasicNetwork.TAG_WEIGHT_INDEX));
+				flat.setWeights(section.parseDoubleArray(params,
+						PersistConst.WEIGHTS));
+				flat.setBiasActivation(section.parseDoubleArray(
+						params, BasicNetwork.TAG_BIAS_ACTIVATION));
+			} else if (section.getSectionName().equals("BASIC")
+					&& section.getSubSectionName().equals("ACTIVATION")) {
+				int index = 0;
+
+				flat.setActivationFunctions(new ActivationFunction[flat
+						.getLayerCounts().length]);
+
+				for (final String line : section.getLines()) {
+					ActivationFunction af = null;
+					final List<String> cols = EncogFileSection
+							.splitColumns(line);
+					final String name = cols.get(0);
+					try {
+						final Class<?> clazz = Class.forName(name);
+						af = (ActivationFunction) clazz.newInstance();
+					} catch (final ClassNotFoundException e) {
+						throw new PersistError(e);
+					} catch (final InstantiationException e) {
+						throw new PersistError(e);
+					} catch (final IllegalAccessException e) {
+						throw new PersistError(e);
+					}
+
+					for (int i = 0; i < af.getParamNames().length; i++) {
+						af.setParam(i,
+								CSVFormat.EG_FORMAT.parse(cols.get(i + 1)));
+					}
+
+					flat.getActivationFunctions()[index++] = af;
+				}
+			}
+		}
+
+		result.getStructure().setFlat(flat);
+		result.updateProperties();
+		
+		return result;
+	}
+
+	/**
+	 * {@inheritDoc}
+	 */
+	@Override
+	public void save(final OutputStream os, final Object obj) {
+		final EncogWriteHelper out = new EncogWriteHelper(os);
+		final BasicNetwork net = (BasicNetwork) obj;
+		final FlatNetwork flat = net.getStructure().getFlat();
+		out.addSection("BASIC");
+		out.addSubSection("PARAMS");
+		out.addProperties(net.getProperties());
+		out.addSubSection("NETWORK");
+
+		out.writeProperty(BasicNetwork.TAG_BEGIN_TRAINING,
+				flat.getBeginTraining());
+		out.writeProperty(BasicNetwork.TAG_CONNECTION_LIMIT,
+				flat.getConnectionLimit());
+		out.writeProperty(BasicNetwork.TAG_CONTEXT_TARGET_OFFSET,
+				flat.getContextTargetOffset());
+		out.writeProperty(BasicNetwork.TAG_CONTEXT_TARGET_SIZE,
+				flat.getContextTargetSize());
+		out.writeProperty(BasicNetwork.TAG_END_TRAINING, flat.getEndTraining());
+		out.writeProperty(BasicNetwork.TAG_HAS_CONTEXT, flat.getHasContext());
+		out.writeProperty(PersistConst.INPUT_COUNT, flat.getInputCount());
+		out.writeProperty(BasicNetwork.TAG_LAYER_COUNTS, flat.getLayerCounts());
+		out.writeProperty(BasicNetwork.TAG_LAYER_FEED_COUNTS,
+				flat.getLayerFeedCounts());
+		out.writeProperty(BasicNetwork.TAG_LAYER_CONTEXT_COUNT,
+				flat.getLayerContextCount());
+		out.writeProperty(BasicNetwork.TAG_LAYER_INDEX, flat.getLayerIndex());
+		out.writeProperty(PersistConst.OUTPUT, flat.getLayerOutput());
+		out.writeProperty(PersistConst.OUTPUT_COUNT, flat.getOutputCount());
+		out.writeProperty(BasicNetwork.TAG_WEIGHT_INDEX, flat.getWeightIndex());
+		out.writeProperty(PersistConst.WEIGHTS, flat.getWeights());
+		out.writeProperty(BasicNetwork.TAG_BIAS_ACTIVATION,
+				flat.getBiasActivation());
+		out.addSubSection("ACTIVATION");
+		for (final ActivationFunction af : flat.getActivationFunctions()) {
+			out.addColumn(af.getClass().getName());
+			for (int i = 0; i < af.getParams().length; i++) {
+				out.addColumn(af.getParams()[i]);
+			}
+			out.writeLine();
+		}
+
+		out.flush();
+	}
+
+}