Read the equation
The source describes this relation in the following context: 5.1 Neural Agent Processing (88 agents)
Each of 88 neural agents processes input through:
F_in = input + N(0, 0.1) // Noisy input
x_old = h[0] // Previous activation
y = y + (x - x_old) - 0.01 × y // Velocity with damping
h[j] = h[j+1] for j=0..42; h[43] = x // Shift hidden state
Terms & definitions
The recovered passage does not supply a separate symbol table. Read the source context for the notation used in this version; familiar letters may carry different meanings in other builds.
How it works
Read F_in as the quantity being defined or updated by this relation.
Substitute the source-defined variables or recorded values and follow the displayed arithmetic and indexing exactly.
Use this version’s variable definitions and update order. The same symbol may be assigned a different meaning in another build.
Assumptions & limits
Source recovery establishes that the expression appears in this record. Its mathematical validity, implementation behavior, and interpretation must be assessed separately. See the linked source and research notes for the checks available for this version.
Original context
Read the surrounding source passage
5.1 Neural Agent Processing (88 agents) Each of 88 neural agents processes input through: F_in = input + N(0, 0.1) // Noisy input x_old = h[0] // Previous activation y = y + (x - x_old) - 0.01 × y // Velocity with damping h[j] = h[j+1] for j=0..42; h[43] = x // Shift hidden state
Exact original notation
F_in = input + N(0, 0.1) // Noisy input
Sources & provenance
F_in = input + N(0, 0.1) // Noisy input