EX#5 A* circuit optimization

  Handouts

LLM 遭遇 多個限制條件的複雜問題 

專注力模型

Comparison of LLMs

Claude Opus 4.6 optimal (visualizing how AI thinks)

Gemini 3.0 Pro 推理，optimal

ChatGPT 5, end results 流程圖  feasible, not optimal，＊

Grok 4 ，end results 流程圖 ＊

Visualization

Decision Tree (share)

location-based time-evolving diagram (space-temporal transformation ), minimalist

animation on map (national & local) share

  課堂練習 

Deadline: This Saturday at 23:59

Send all the share links to  me chang212@gmail.com by email with subject EX#5 [your id, your name]

1. Design a Two-Stage BJT Amplifier according to goals specified using A* (Parameters to optimize RE1, RC1. RE2. RC2) 

A* search for optimization, share  (c_mu=3 pF, c_pi=22 pF)

2. Optimize LM3886 class AB audio amplifier IC using A* (Parameters to optimize: resistors except the load) 

LM3886

A Search Setup*

• State space: 5 components × 5 E12 values each = 3,125 possible states
• g(n): actual steps taken from the start configuration
• h(n): circuit performance cost (the heuristic) — sum of 5 weighted penalties
• f(n) = g + h: A* priority queue ordering

Cost function (5 components, all minimized):

• Gain: quadratic penalty for deviation from 26 dB (20×)
• f_low: penalty if low-frequency cutoff exceeds 10 Hz
• f_high: penalty if high-frequency cutoff falls below 100 kHz
• Bias: penalizes Rb1 ≠ Rb2 (asymmetric thermal tracking)
• Re stability: log-scale penalty away from 0.47 Ω optimum

Weight/ Forms

Are Re1 and Re2 Always Equal?

the architecture inside the LM3886 and TDA7293

optimizer A* (share)