inputDimensions
A sequence representing the dimensions of the input vector. Format is
(height, width, depth, ...), where each value represents the size of the
dimension. For a topology of one dimension with 100 inputs use 100, or
(100,). For a two dimensional topology of 10x5 use (10,5).
Values depend on dimensions of encodings.
columnDimensions
A sequence representing the dimensions of the columns in the region.
Format is (height, width, depth, ...), where each value represents the
size of the dimension. For a topology of one dimension with 2000 columns
use 2000, or (2000,). For a three dimensional topology of 32x64x16 use
(32, 64, 16).
- sane default:
[2048] - min:
? - max:
?
potentialRadius
This parameter determines the extent of the input that each column can
potentially be connected to. This can be thought of as the input bits
that are visible to each column, or a 'receptiveField' of the field of
vision. A large enough value will result in 'global coverage', meaning
that each column can potentially be connected to every input bit. This
parameter defines a square (or hyper
square) area: a column will have a max square potential pool with sides of
length 2 * potentialRadius + 1.
- sane default:
16 - min:
? - max:
?
potentialPct (âpotential percentâ)
The percent of the inputs, within a column's potential radius, that a
column can be connected to. If set to 1, the column will be connected
to every input within its potential radius. This parameter is used to
give each column a unique potential pool when a large potentialRadius
causes overlap between the columns. At initialization time we choose
((2*potentialRadius + 1)^(# inputDimensions) * potentialPct) input bits
to comprise the column's potential pool.
- sane default:
0.85 - min:
0.0 - max:
1.0
globalInhibition
If true, then during inhibition phase the winning columns are selected
as the most active columns from the region as a whole. Otherwise, the
winning columns are selected with respect to their local neighborhoods.
Using global inhibition boosts performance x60.
- sane default:
true
localAreaDensity
The desired density of active columns within a local inhibition area
(the size of which is set by the internally calculated inhibitionRadius,
which is in turn determined from the average size of the connected
potential pools of all columns). The inhibition logic will insure that
at most N columns remain ON within a local inhibition area, where
N = localAreaDensity * (total number of columns in inhibition area).
- sane default:
-1.0 - min:
? - max:
? - linked to
numActiveColumnsPerInhArea
numActiveColumnsPerInhArea (ânumber of active columns per inhibition areaâ)
An alternate way to control the density of the active columns. If
numActiveColumnsPerInhArea is specified then localAreaDensity must be
less than 0, and vice versa. When using numActiveColumnsPerInhArea, the
inhibition logic will insure that at most 'numActiveColumnsPerInhArea'
columns remain ON within a local inhibition area (the size of which is
set by the internally calculated inhibitionRadius, which is in turn
determined from the average size of the connected receptive fields of all
columns). When using this method, as columns learn and grow their
effective receptive fields, the inhibitionRadius will grow, and hence the
net density of the active columns will *decrease*. This is in contrast to
the localAreaDensity method, which keeps the density of active columns
the same regardless of the size of their receptive fields.
- sane default:
10.0 - min:
? - max:
? - linked to
localAreaDensity
stimulusThreshold
This is a number specifying the minimum number of synapses that must be
on in order for a columns to turn ON. The purpose of this is to prevent
noise input from activating columns. Specified as a percent of a fully
grown synapse.
- sane default:
0 - min:
0 - max:
?
synPermInactiveDec (âsynapse permanence inactive decrementâ)
The amount by which an inactive synapse is decremented in each round.
Specified as a percent of a fully grown synapse.
- sane default:
0.008 - min:
0.0 - max:
?
synPermActiveInc (âsynapse permanence active incrementâ)
The amount by which an active synapse is incremented in each round.
Specified as a percent of a fully grown synapse.
- sane default:
0.05 - min:
0.0 - max:
?
synPermConnected (âsynapse permanence connectedâ)
The default connected threshold. Any synapse whose permanence value is
above the connected threshold is a "connected synapse", meaning it can
contribute to the cell's firing.
- sane default:
0.10 - min:
0.0 - max:
?
minPctOverlapDutyCycle (âminimum percent overlap duty cycleâ)
A number between 0 and 1.0, used to set a floor on how often a column
should have at least stimulusThreshold active inputs. Periodically, each
column looks at the overlap duty cycle of all other columns within its
inhibition radius and sets its own internal minimal acceptable duty cycle
to: minPctDutyCycleBeforeInh * max(other columns' duty cycles). On each
iteration, any column whose overlap duty cycle falls below this computed
value will get all of its permanence values boosted up by
synPermActiveInc. Raising all permanences in response to a sub-par duty
cycle before inhibition allows a cell to search for new inputs when
either its previously learned inputs are no longer ever active, or when
the vast majority of them have been "hijacked" by other columns.
- sane default:
0.001 - min:
0.0 - max:
1.0
minPctActiveDutyCycle (âminimum percent active duty cycleâ)
A number between 0 and 1.0, used to set a floor on how often a column
should be activate. Periodically, each column looks at the activity duty
cycle of all other columns within its inhibition radius and sets its own
internal minimal acceptable duty cycle to: minPctDutyCycleAfterInh *
max(other columns' duty cycles). On each iteration, any column whose duty
cycle after inhibition falls below this computed value will get its
internal boost factor increased.
- sane default:
0.001 - min:
0.0 - max:
1.0
dutyCyclePeriod
The period used to calculate duty cycles. Higher values make it take
longer to respond to changes in boost or synPerConnectedCell. Shorter
values make it more unstable and likely to oscillate.
- sane default:
1000 - min:
? - max:
?
maxBoost
The maximum overlap boost factor. Each column's overlap gets multiplied
by a boost factor before it gets considered for inhibition. The actual
boost factor for a column is number between 1.0 and maxBoost. A boost
factor of 1.0 is used if the duty cycle is >= minOverlapDutyCycle,
maxBoost is used if the duty cycle is 0, and any duty cycle in between is
linearly extrapolated from these 2 endpoints.
- sane default:
1.0 - min:
0.0 - max:
?
