Diff: NeuroShield.h

Revision:

0:529602524696

Child:

1:0c6bf23f2fc8

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/NeuroShield.h	Thu Aug 17 23:31:15 2017 +0000
@@ -0,0 +1,123 @@
+/*
+ * NeuroShield.cpp - Driver for NeuroShield
+ * Copyright (c) 2016, General Vision Inc, All rights reserved
+ * Copyright (c) 2017, nepes inc, All rights reserved.
+ *
+ * Redistribution and use in source and binary forms, with or without
+ * modification, are permitted provided that the following conditions are met:
+ *
+ * 1. Redistributions of source code must retain the above copyright notice,
+ * this list of conditions and the following disclaimer.
+ *
+ * 2. Redistributions in binary form must reproduce the above copyright notice,
+ * this list of conditions and the following disclaimer in the documentation
+ * and/or other materials provided with the distribution.
+ *
+ * 3. Neither the name of the copyright holder nor the names of its contributors
+ * may be used to endorse or promote products derived from this software without
+ * specific prior written permission.
+ *
+ * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+ * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+ * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+ * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
+ * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+ * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+ * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+ * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+ * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+ * POSSIBILITY OF SUCH DAMAGE.
+ *
+ */
+
+#ifndef _NEUROSHIELD_H
+#define _NEUROSHIELD_H
+
+#include <NeuroShieldSPI.h>
+
+#define NM_NCR          0x00
+#define NM_COMP         0x01
+#define NM_LCOMP        0x02
+#define NM_DIST         0x03
+#define NM_INDEXCOMP    0x03
+#define NM_CAT          0x04
+#define NM_AIF          0x05
+#define NM_MINIF        0x06
+#define NM_MAXIF        0x07
+#define NM_TESTCOMP     0x08
+#define NM_TESTCAT      0x09
+#define NM_NID          0x0A
+#define NM_GCR          0x0B
+#define NM_RSTCHAIN     0x0C
+#define NM_NSR          0x0D
+#define NM_POWERSAVE    0x0E
+#define NM_NCOUNT       0x0F
+#define NM_FORGET       0x0F
+
+#define NEURON_SIZE     256     // memory capacity of each neuron in byte
+
+class NeuroShield
+{
+    public:
+    
+        NeuroShield();
+        uint16_t begin();
+        
+        void setNcr(uint16_t value);
+        uint16_t getNcr();
+        void setComp(uint8_t value);
+        uint8_t getComp();
+        void setLastComp(uint8_t value);
+        void setIndexComp(uint16_t value);
+        uint16_t getDist();
+        void setCat(uint16_t value);
+        uint16_t getCat();
+        void setAif(uint16_t value);
+        uint16_t getAif();
+        void setMinif(uint16_t value);
+        uint16_t getMinif();
+        void setMaxif(uint16_t value);
+        uint16_t getMaxif();
+        uint16_t getNid();
+        void setGcr(uint16_t value);
+        uint16_t getGcr();
+        void resetChain();
+        void setNsr(uint16_t value);
+        uint16_t getNsr();
+        uint16_t getNcount();
+        void setPowerSave();
+        void forget();
+        void forget(uint16_t maxif);
+        
+        void countTotalNeurons();
+        void clearNeurons();
+        
+        void setContext(uint8_t context);
+        void setContext(uint8_t context, uint16_t minif, uint16_t maxif);
+        void getContext(uint8_t* context, uint16_t* minif, uint16_t* maxif);
+        void setRbfClassifier();
+        void setKnnClassifier();
+        
+        uint16_t broadcast(uint8_t vector[], uint16_t length);
+        uint16_t learn(uint8_t vector[], uint16_t length, uint16_t category);
+        uint16_t classify(uint8_t vector[], uint16_t length);
+        uint16_t classify(uint8_t vector[], uint16_t length, uint16_t* distance, uint16_t* category, uint16_t* nid);
+        uint16_t classify(uint8_t vector[], uint16_t length, uint16_t k, uint16_t distance[], uint16_t category[], uint16_t nid[]);
+        
+        void readNeuron(uint16_t nid, uint8_t model[], uint16_t* ncr, uint16_t* aif, uint16_t* cat);
+        void readNeuron(uint16_t nid, uint8_t nuerons[]);
+        uint16_t readNeurons(uint8_t neurons[]);
+        uint16_t writeNeurons(uint8_t neurons[]);
+        
+        uint16_t testCommand(uint8_t read_write, uint8_t reg, uint16_t data);
+        
+        uint16_t fpgaVersion();
+        void nm500Reset();
+        void ledSelect(uint8_t data);
+        
+        void displayNeurons(uint16_t length);
+        
+        uint16_t total_neurons;
+};
+#endif
\ No newline at end of file