本人編寫的incremental 隨機神經元網絡算法，該算法最大的特點是可以保證approximation特性，而且速度快效果不錯，可以作為學術上的比較和分析。目前只適合benchmark的regression問題。
具體效果可參考
G.-B. Huang, L. Chen and C.-K. Siew, “Universal Approximation Using Incremental Constructive Feedforward Networks with Random Hidden Nodes”, IEEE Transactions on Neural Networks, vol. 17, no. 4, pp. 879-892, 2006.
標簽：
incremental
編寫
神經元網絡
算法
上傳時間：
2016-09-18
上傳用戶：litianchu
The DHRY program performs the dhrystone benchmarks on the 8051.
Dhrystone is a general-performance benchmark test originally
developed by Reinhold Weicker in 1984. This benchmark is
used to measure and compare the performance of different
computers or, in this case, the efficiency of the code
generated for the same computer by different compilers.
The test reports general performance in dhrystones per second.
Like most benchmark programs, dhrystone consists of standard
code and concentrates on string handling. It uses no
floating-point operations. It is heavily influenced by
hardware and software design, compiler and linker options,
code optimizing, cache memory, wait states, and integer
data types.
The DHRY program is available in different targets:
Simulator: Large Model: DHRY example in LARGE model
for Simulation
Philips 80C51MX: DHRY example in LARGE model
for the Philips 80C51MC
標簽：
general-performanc
benchmarks
Dhrystone
dhrystone
上傳時間：
2016-11-30
上傳用戶：hphh
