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java.lang.Objectedu.memphis.ccrg.lida.episodicmemory.sdm.SparseDistributedMemoryImpl
public class SparseDistributedMemoryImpl
Implementation of Kanerva's sparse distributed memory. This implementation is based on the model described in P. Kanerva, "Sparse Distributed Memory and Related Models" in Associative Neural Memories: Theory and Implementation , pp. 50-76, Oxford University Press, 1993.
Constructor Summary | |
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SparseDistributedMemoryImpl(int memorySize,
int radius,
int wordLength)
Constructor of the class that receives all the parameters necessary for this sparse distributed memory. |
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SparseDistributedMemoryImpl(int memorySize,
int radious,
int wordLength,
int addrLength)
Constructor of the class that receives all the parameters necessary for this sparse distributed memory. |
Method Summary | |
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void |
mappedStore(cern.colt.bitvector.BitVector wrd,
cern.colt.bitvector.BitVector mapping)
Stores word in this sparse distributed memory using the word as address. |
cern.colt.bitvector.BitVector |
retrieve(cern.colt.bitvector.BitVector addr)
Retrieves the contents of this sparse distributed memory at the given address. |
cern.colt.bitvector.BitVector |
retrieve(cern.colt.bitvector.BitVector addr,
cern.colt.bitvector.BitVector mapping)
Retrieves the contents of this SDM at addr. |
cern.colt.bitvector.BitVector |
retrieveIterating(cern.colt.bitvector.BitVector addr)
Retrieves the contents of this sparse distributed memory at the given address iterating this process until result is equal to the address. |
cern.colt.bitvector.BitVector |
retrieveIterating(cern.colt.bitvector.BitVector addr,
cern.colt.bitvector.BitVector mapping)
Retrieves the contents of this SDM at addr. |
void |
store(cern.colt.bitvector.BitVector wrd)
Stores word in this sparse distributed memory using the word as address. |
void |
store(cern.colt.bitvector.BitVector wrd,
cern.colt.bitvector.BitVector addr)
Stores word in the given address in this sparse distributed memory. |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public SparseDistributedMemoryImpl(int memorySize, int radius, int wordLength)
memorySize
- the size of the memoryradius
- the activation radiuswordLength
- the word sizepublic SparseDistributedMemoryImpl(int memorySize, int radious, int wordLength, int addrLength)
memorySize
- the size of the memoryradious
- the activation radiuswordLength
- the word sizeaddrLength
- the address sizeMethod Detail |
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public void store(cern.colt.bitvector.BitVector wrd, cern.colt.bitvector.BitVector addr)
SparseDistributedMemory
store
in interface SparseDistributedMemory
wrd
- the word to be storedaddr
- the address where the word is to be storedpublic void store(cern.colt.bitvector.BitVector wrd)
SparseDistributedMemory
store
in interface SparseDistributedMemory
wrd
- the word to be storedpublic void mappedStore(cern.colt.bitvector.BitVector wrd, cern.colt.bitvector.BitVector mapping)
SparseDistributedMemory
mappedStore
in interface SparseDistributedMemory
wrd
- the word to be stored.mapping
- the mapping address.public cern.colt.bitvector.BitVector retrieve(cern.colt.bitvector.BitVector addr)
SparseDistributedMemory
retrieve
in interface SparseDistributedMemory
addr
- the address of the contents to be retrieved
public cern.colt.bitvector.BitVector retrieve(cern.colt.bitvector.BitVector addr, cern.colt.bitvector.BitVector mapping)
SparseDistributedMemory
retrieve
in interface SparseDistributedMemory
addr
- the address vectormapping
- the mapping vector
public cern.colt.bitvector.BitVector retrieveIterating(cern.colt.bitvector.BitVector addr)
SparseDistributedMemory
retrieveIterating
in interface SparseDistributedMemory
addr
- the address of the contents to be retrieved
public cern.colt.bitvector.BitVector retrieveIterating(cern.colt.bitvector.BitVector addr, cern.colt.bitvector.BitVector mapping)
SparseDistributedMemory
retrieveIterating
in interface SparseDistributedMemory
addr
- bitvector address that is being retreivedmapping
- mapping to use
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