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In this video, we implement an entire layer of a feed-forward neural network by reusing the exact same hardware from the single-neuron design. The key idea is that a layer is just the same neuron calculation repeated multiple times, one time per neuron, with different weights and biases each time. ✅ Subscribe for weekly FPGA / Verilog projects as the course expands. 📺 Full Playlist: • Advanced FPGA Course: Verilog Based Roboti... 💎 Unlock the Full Course Experience 💎 ✔ Extended lessons ✔ Worksheets + assignments ✔ Private Discord community ✔ Lifetime access to all updates 💻 Digital Editions (Instant Access + Discount): • 📗 Introduction to Verilog — 30% Off: https://buy.stripe.com/4gM28ta5c3rMdq... • 📘 Verilog-Based Robotics & Signal Processing — 50% Off: https://buy.stripe.com/7sY9AVa5c1jEdq... 📚 Physical Editions (Amazon): • 📗 Introduction to Verilog: https://www.amazon.com/dp/B0D92325VC • 📘 Verilog-Based Robotics & Signal Processing: https://www.amazon.com/dp/B0F7QVT2T8 🎓 Who This Course Is For • Electrical & Computer Engineering students • FPGA engineers seeking real project experience • Intermediate Verilog users ready for expert-level skills • Anyone preparing for a career in FPGA/ASIC hardware design ⏱️ Video Chapters 0:00 – Intro 1:00 – Promotion 1:39 – Last Video Recap 2:45 – Layer Calculator Module 6:39 – Pulse Generator Module #FPGA #Verilog #PIDController #Artix7 #ControlSystems #ADC #SignalProcessing #DigitalDesign #Robotics