健康照護科技專題，盲人導航，Robot Nav, 射頻ＩＣ設計: 4月 2026

2026年4月28日星期二

HW#8 Claude Cowork

課堂練習

Deadline: This Saturday at 23:59

Send all the share links to me chang212@gmail.com by email with subject HW#8 [your id, your name]

Part 1

Use Claude CoWork to benchmark BJT Differential Pair

1. Experiments with 30 seeds

schematic with parameter optimizer

2. The SA code is flawed. Therefore Ad, CMRR, PM cannot be optimized. Use Cowork to diagnose and fix the code. Rerun the bencmark.

Hint: prompts for CoWork

Prompts for Claude Chat

Part 2

Benchmark the P&R for OP 741.

Experiment with 3 seeds

Measure success, congestions, wirelength, overlap pairs (before/after), Vin length match

Placer & Router for OP 741

benchmark

2026年4月27日星期一

AI Tool Decision

cowork vs. chat, projector friendly

py & bash execution tool use & container, projector friendly

cowork vs openclaw, projector friendly

2026年4月19日星期日

SWERV RISC IC Design

baseline macro 32, metal layers 3, die 550 × 600 μm

add timing

add CTS

add std cells

add logistic prob of wins

Bit sliced macro 28, metal layers 9, die 690 × 750 μm

2026年4月17日星期五

Optimize PCB trace routing for the Differential Pair Circuit on PCB

Components on PCB

imperfect design

schematic fix

Make it layer-aware with two layers

Add Pathfinder

eliminate phantom

trace routing, share, share 2, share 3

2026年4月14日星期二

Common issues in BJT diff pair design

BJT diff pair

Routing

(by TA)

1. unfinished routing

2. one stage diff pair 是沒有 miller 電容 cc

miller 電容在 stage 2

Parameter Optimization

(by TA)

1. SA 是無效的

檢查sa 效能

2. 檢查是否合規

gain 47.6 db 不夠

PM 0 很危險，不穩定

GBW 太大

設計目標 (3.3V):
Ad ≥ 50 dB  |  CMRR ≥ 80 dB
GBW ≥ 100 MHz  |  PM 55°–75°
Vos ≤ 1 mV  |  Pd ≤ 20 mW
Poly R: 250 Ω/sq (±20%)
MIM C: 1 fF/μm² (±15%)


refer to sample

2026年4月13日星期一

HW#7 Analog IC Design

課堂練習

Deadline: This Saturday at 23:59

Send all the share links to me chang212@gmail.com by email with subject HW#6 [your id, your name]

任選1題

1 (a) A BJT Differential Pair IC Die (share) is incorrectly designed. Fix the die.

(b) Make a schematic

(d) Placement & Routing for the die

For example you may use Quadratic Placement & ILP+PathFinder+A* Routing

2. Design 2-stage diff pair (share from very simple diff pair)

(a) Make a schematic,

(b) Draw a silicon die, considering Miller Compensation,

See example of P&R+opt compo

2026年4月8日星期三

健康照護科技專題(二) Syllabus 2026 Fall

張耀仁教授

這些主題都以 AI 輔助、不需自行撰寫底層程式

本課程限定使用 Claude AI，有特殊原因必須使用其他ＡＩ者需在選課前與老師商量。

開場

Unit 1: AI Computer Vision, 1 week

CNN (Convolutional Neural Networks) Handwashing

YOLO (You Only Look Once) YOLOv7 list

ViT (Vision Transformers) wafer defects heat map comparison

VLM (Vision Language Models) nutrition analysis

Tesla AI Vision

HW#1 AI in Computer Vision

Unit 2: 盲人環境輔助理解，空間導航, 1 week

真實世界 3d 模型製作

3d 導航(why 3D)

HW#2 Understanding environments

Unit 3: 3d障礙偵測演算法, 1 week

3d障礙全域分析

Simulating A Navigation Assistant with sonar

HW#3 Obstacle detection

Unit 4: Voronoi 避障演算法, 1 week

Voronoi

Voronoi 2D navigation (show Voronoi) (Rural Road 2d)

Voronoi-based Safe Routing Planning (Country Alley 2d)

Voronoi waypoints for navigation (share) (Campus Alley 3d) vs. non Voronoi

3D Voronoi障礙偵測 with A*

A* search for Voronoi Navigation around moving obstacles

Unit 5: 環境安全檢測與評估視覺化 using Claude, 1 week

Hazard detection (環境危害偵測)

意外事件預測與模擬

Home Hazard chain identification and animation （居家危害鏈偵測與危害視覺化）

Unit 6: World Model for Artificial General Intelligence (AGI), 3 weeks

Unit 7: AI for Game Designing, 2 weeks

Games

Unit 8 Space-Time Evolution, 2 weeks

Unit 9 Advanced Prompts, 1 week

How to scale up: Compound Artifacts

如何合成複雜創作

Unit 10

AI for Academic Documentation, 2 weeks

Unit 11 Machine Learning for Asset Management, 2 weeks

__________________________________________________________________

本專題課程以 AI 輔助探討健康照護科技之應用，涵蓋 AI 電腦視覺、盲人環境輔助理解與空間導航、3D 障礙偵測與避障演算法（Voronoi、A*）、環境安全與居家危害偵測視覺化、World Model (AGI)、健康促進遊戲設計、以及 AI 學術論文寫作等主題，從實作中培養運用 AI 解決健康照護相關問題的能力。

backup

AI Pipe Robot

Anthropology

Human migration

Design

2026年4月7日星期二

HW#6 A* Circuit Optimization

本次作業詳細說明

課堂練習

Deadline: This Saturday at 23:59

Send all the share links to me chang212@gmail.com by email with subject HW#6 ［your id, your name]

任選一題

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)

Lessons learned from AI use

Lesson 1

Design a Two-Stage BJT Amplifier (Parameters to optimizeRE1, RC1. RE2. RC2)

Note this is a degenerate model

A* search for optimization, share 4-parameter (for bypassed model c_mu=3 pF, c_pi=22 pF) note: goal reached is actually current step, not current best